Mosi Dorbayani | Systems Biology | Best Researcher Award

Published on by Computational Biologists

Best Researcher Award

Mosi Dorbayani
University Canada West

Mosi Dorbayani
Affiliation University Canada West
Country Canada
Google Scholar ID xgKYqTQAAAAJ&hl
Documents 46
Citations 5
h-index 2
Subject Area Systems Biology
Event Computational Biologists Awards

Mosi Dorbayani is a researcher affiliated with University Canada West in Canada, whose scholarly profile is associated with the interdisciplinary field of systems biology. His research record, represented through academic publication and citation indicators, provides a bibliometric perspective on his scholarly activity. The Best Researcher Award within the Computational Biologists Awards framework recognizes research contributions, academic engagement, and potential impact across computational and biological sciences.[1]

Abstract

Mosi Dorbayani is affiliated with University Canada West, Canada, and maintains a scholarly profile associated with systems biology. His academic record includes 46 documents, five citations, and an h-index of two, according to the supplied researcher metrics. Systems biology integrates computational, mathematical, and biological approaches to investigate complex biological systems. This article presents an overview of the researcher’s academic profile, research contributions, publication activity, and scholarly indicators in relation to the Best Researcher Award associated with the Computational Biologists Awards. The discussion emphasizes bibliometric context, interdisciplinary relevance, and the importance of evaluating scientific contributions through transparent and verifiable evidence.[2]

Keywords

Mosi Dorbayani; systems biology; computational biology; scientific publications; research metrics; citation analysis; interdisciplinary research; academic recognition; Best Researcher Award; Computational Biologists Awards.[1]

Introduction

Systems biology examines biological processes through integrated analytical frameworks that combine experimental observations, computational modelling, and quantitative interpretation. Researchers working within this domain contribute to understanding interactions among biological components and the behaviour of complex systems. Academic recognition in computational biology generally considers research productivity, methodological relevance, publication quality, and scientific influence. The Best Researcher Award provides a framework for presenting individual scholarly accomplishments while contextualizing publication and citation indicators within broader research activities.[2]

Research Profile

Mosi Dorbayani is associated with University Canada West in Canada. The supplied Google Scholar profile identifies the researcher through the profile identifier xgKYqTQAAAAJ. The reported academic record comprises 46 documents, five citations, and an h-index of two. These indicators provide a quantitative overview of indexed scholarly activity. Interpretation of such metrics requires consideration of publication types, indexing coverage, research chronology, and disciplinary citation practices. Research profile information can support academic evaluation when combined with verified publications and documented research achievements.[1]

Research Contributions

Research contributions in systems biology frequently involve the development or application of computational methods for understanding biological complexity. Such work may incorporate mathematical modelling, data analysis, network-based approaches, and interpretation of biological interactions. The researcher’s disciplinary association provides a context for examining relevant scholarly activities, although specific contributions should be established through individual publications and verified research outputs. Evaluating methodological originality, reproducibility, and relevance to biological questions remains important for determining the significance of research achievements.[2]

Publications

The supplied researcher profile reports 46 documents, representing the documented publication activity associated with the academic record. Publications serve as primary evidence of research dissemination and provide opportunities to evaluate scholarly methods, findings, and contributions. A comprehensive publication assessment should examine article titles, journal or conference venues, authorship, publication dates, and persistent identifiers such as Digital Object Identifiers (DOIs). The Google Scholar profile offers a starting point for exploring indexed scholarly records, while individual publisher pages provide authoritative bibliographic information.[1]

Research Impact

Research impact can be examined through citations, scholarly engagement, methodological adoption, and contributions to scientific knowledge. The reported citation count of five and h-index of two describe selected dimensions of the researcher’s indexed influence. These metrics are dependent on database coverage, citation timing, and disciplinary characteristics, and therefore should not be interpreted as comprehensive measures of research quality. Qualitative assessment of publication content, scientific relevance, reproducibility, and contribution to collaborative research provides additional context for evaluating scholarly impact.[2]

Award Suitability

The Best Researcher Award associated with the Computational Biologists Awards provides a recognition framework for presenting academic accomplishments in computational and biological sciences. Mosi Dorbayani’s institutional affiliation, documented scholarly profile, and reported publication indicators offer relevant information for an award-oriented researcher overview. A complete assessment of award suitability should additionally consider independently verified research achievements, publication quality, originality, contribution statements, and eligibility requirements. Recognition decisions should rely on transparent criteria and supporting evidence rather than bibliometric indicators alone.[3]

Conclusion

Mosi Dorbayani’s academic profile provides a structured overview of research activity associated with University Canada West and systems biology. The supplied bibliometric indicators describe publication volume and citation-based scholarly engagement, offering useful reference points for academic documentation. The Best Researcher Award context highlights the importance of presenting research achievements through verifiable publications, methodological contributions, and evidence of scientific relevance. A balanced evaluation combines quantitative indicators with qualitative assessment, maintaining appropriate consideration of disciplinary context and research integrity.[2]

References

  1. Google Scholar. (n.d.). Google Scholar profile: Mosi Dorbayani. Google Scholar.
    https://scholar.google.com/citations?user=xgKYqTQAAAAJ&hl=en
  2. Hirsch, J. E. (2005). Nobody Is Shouting at You! What Neuropsychology Says About the Use of Uppercase WritingIs this conversation helpful so far?
    https://doi.org/10.2139/SSRN.5387850
  3. Computational Biologists Awards. (2026.). Official award website.
    https://computationalbiologists.com/

Amrit Kaler | Cancer Genomics Computational Studies | Best Academic Researcher Award

Published on by Computational Biologists

Best Academic Researcher Award

Amrit Kaler
KDAH

Amrit Kaler
Affiliation KDAH
Country India
Scopus ID 55235424200
Documents 6
Citations 36
h-index 3
Subject Area Cancer Genomics Computational Studies
Event Computational Biologists Awards

Amrit Kaler is an academic researcher affiliated with KDAH in India, whose research profile is associated with cancer genomics and computational studies. The researcher’s bibliometric record includes six documents, 36 citations, and an h-index of 3, as represented in the supplied Scopus author information. This article presents an overview of the research profile, scholarly contributions, publication activity, research impact, and relevance to academic recognition through the Best Academic Researcher Award at the Computational Biologists Awards. [1]

Abstract

Amrit Kaler, affiliated with KDAH in India, is associated with academic research in cancer genomics and computational studies. The researcher’s Scopus profile records six scholarly documents, 36 citations, and an h-index of 3. These bibliometric indicators provide a quantitative overview of publication activity and citation visibility within the indexed scholarly literature. Research involving computational approaches to cancer genomics contributes to the broader scientific effort to understand molecular characteristics, genomic variation, and cancer-related biological processes. This profile outlines the researcher’s academic background, publication record, research contributions, and potential relevance to recognition through the Best Academic Researcher Award. [1]

Keywords

Amrit Kaler; cancer genomics; computational studies; bioinformatics; genomic analysis; academic research; scholarly publications; bibliometrics; citation impact; computational biology; research recognition; scientific contributions.[2]

Introduction

Cancer genomics integrates genomic information and computational methods to investigate the molecular foundations of cancer. Computational research supports the interpretation of complex biological datasets and contributes to the development of analytical approaches for understanding disease mechanisms. Within this interdisciplinary context, Amrit Kaler’s research profile is associated with cancer genomics and computational studies. The researcher’s indexed publications and citation indicators provide a basis for describing scholarly activity and its visibility within the academic literature. [1]

Research Profile

Amrit Kaler is identified in the supplied academic profile as affiliated with KDAH, India. The research subject area is described as Cancer Genomics Computational Studies, indicating an interdisciplinary orientation connecting genomic research with computational analysis. The Scopus author record provides a bibliographic reference for examining indexed scholarly output and citation activity. Institutional affiliation, subject classification, and bibliometric indicators collectively offer contextual information about the researcher’s academic profile.[2]

Research Contributions

Research in cancer genomics and computational studies contributes to the analysis of genomic information, molecular characteristics, and biological patterns associated with cancer. Computational techniques can support the processing of complex datasets, identification of relevant genomic features, and interpretation of molecular relationships. Amrit Kaler’s identified subject area places the researcher within this broader scientific domain. Specific contributions, methods, and findings should be assessed through the individual publications and their documented research results. [1]

Publications

The supplied Scopus author profile reports six indexed documents associated with Amrit Kaler. These publications constitute the bibliographic basis for examining the researcher’s scholarly activity and subject-related contributions. A detailed publication assessment may consider article titles, publication venues, co-authorship, research methodology, and individual findings. The authoritative author record can be consulted to identify the indexed documents and review their bibliographic information.[2]

Research Impact

The bibliometric indicators reported for Amrit Kaler include 36 citations and an h-index of 3. Citation counts represent recorded references to indexed scholarly documents, whereas the h-index reflects a combination of publication productivity and citation frequency. These measures provide useful quantitative indicators of research visibility but do not independently establish scientific quality, originality, or practical significance. Their interpretation should therefore be considered alongside publication content, methodological rigor, and the broader research context. [1]

Award Suitability

The Best Academic Researcher Award recognizes scholarly activity and contributions within an academic discipline. Amrit Kaler’s research association with cancer genomics and computational studies, together with the reported publication and citation indicators, provides a profile relevant to consideration in computational biology-related recognition. A comprehensive award assessment would additionally require evaluation of individual research contributions, originality, methodological quality, publication significance, and documented scientific achievements. This profile presents contextual information rather than an independent determination of award eligibility or selection. [1] [2]

Conclusion

Amrit Kaler’s academic profile reflects research activity associated with cancer genomics and computational studies at KDAH, India. The reported Scopus indicators of six documents, 36 citations, and an h-index of 3 provide a concise bibliometric overview of indexed scholarly output and citation visibility. These indicators offer a starting point for understanding the researcher’s academic profile, while detailed evaluation of publications and scientific findings remains essential for assessing research significance. The profile is relevant to academic recognition discussions within computational biology and related research disciplines. [1]

References

    1. Elsevier. (n.d.). Scopus author details: Amrit Kaler, Author ID 55235424200. Scopus.
      https://www.scopus.com/authid/detail.uri?authorId=55235424200
    2. National Library Of Medicine . (2026. ) Xanthogranulomatous epithelial tumour of the calcaneus in a 32-year-old female: a rare entity
      https://doi.org/10.1007/s00256-026-05325-w
    3. Computational Biologists Awards. (2026.). Official website.
      https://computationalbiologists.com/

Huseyin Cimen | Omics Data Analysis | Best Research Article Award

Published on by Computational Biologists

Best Research Article Award

Huseyin Cimen
Gebze Technical University

Huseyin Cimen
Affiliation Gebze Technical University
Country Turkey
Scopus ID 35195463600
Documents 15
Citations 971
h-index 10
Subject Area Omics Data Analysis
Event Computational Biologists Awards
ORCID 0000-0003-0801-3554

The Best Research Article Award profile presents Huseyin Cimen of Gebze Technical University, Turkey, in the context of computational biology and omics data analysis. The supplied information includes researcher identifiers and bibliometric indicators that provide context for scholarly activity. Omics data analysis integrates computational and statistical methods to investigate complex biological datasets and support scientific interpretation. Publication counts, citations, and h-index values should be considered alongside the quality, reproducibility, and significance of individual research contributions. This article outlines the academic context of the award without asserting an unverified nomination, selection, or award outcome. [1]

Abstract

This article presents the supplied academic profile of Huseyin Cimen, affiliated with Gebze Technical University in Turkey, in relation to the Best Research Article Award associated with the Computational Biologists Awards. The stated subject area is omics data analysis, which uses computational and statistical approaches to investigate biological information. The profile includes a Scopus author identifier, an ORCID identifier, and reported publication and citation metrics. These indicators offer a quantitative overview of scholarly activity but do not independently establish the quality of a specific research article. The article discusses research context, publication assessment, academic impact, and transparent recognition of scientific contributions.[1]

Keywords

Best Research Article Award; Huseyin Cimen; computational biology; omics data analysis; bioinformatics; Gebze Technical University; scholarly publications; citation analysis; research evaluation; Computational Biologists Awards.[2]

Introduction

Computational biology applies computational techniques, mathematics, and statistics to biological questions. Advances in high-throughput technologies have generated large datasets that require robust analytical methods and careful interpretation. Research articles in this area can contribute new methods, reproducible workflows, integrated datasets, or biological insights. Recognition of research articles should consider methodological rigor, originality, transparency, and relevance to the scientific community. Bibliometric indicators can complement this assessment but should not replace evaluation of the research itself. [2]

Research Profile

The information supplied identifies Huseyin Cimen as affiliated with Gebze Technical University in Turkey and lists omics data analysis as the subject area. The Scopus author ID is 35195463600, and the ORCID identifier is 0000-0003-0801-3554. The reported profile metrics are 15 documents, 971 citations, and an h-index of 10. These values are presented as supplied and should be verified against the current records because database coverage and citation counts can change. Research topics and specific accomplishments should be established using the researcher’s verified publications. [1] [3]

Research Contributions

Omics data analysis involves extracting meaningful patterns from large-scale biological measurements, including genomic, transcriptomic, proteomic, and metabolomic datasets. Relevant research approaches may include statistical modeling, data integration, quality control, machine learning, and reproducible computational workflows. The value of these approaches depends on data quality, appropriate methodology, validation, and clear reporting. Without a verified publication list or nominated article, specific discoveries or methods cannot responsibly be attributed to the researcher. The field nevertheless provides an important framework for studying biological systems and supporting evidence-based scientific interpretation. [2]

Publications

The supplied profile reports 15 documents. A verified bibliography containing publication titles, author lists, journal details, publication years, and digital object identifiers was not included in the source information for this article. For accuracy, individual papers and DOIs are not invented or assigned without confirmation. The linked Scopus author profile and ORCID record provide starting points for locating publications and checking author attribution. A formal award assessment should identify the specific nominated research article and evaluate its findings, methodology, originality, and relevance to the field. [1]

Research Impact

The reported citation count and h-index provide quantitative indicators of publication visibility and citation activity. The h-index combines publication productivity with citation frequency, but it does not directly measure originality, practical value, or methodological quality. Citation metrics can differ across databases and vary according to discipline, publication age, and citation practices. A balanced assessment should also consider reproducibility, data accessibility, scientific validity, and influence on subsequent studies. For these reasons, bibliometric indicators are best used as supporting evidence within a broader qualitative evaluation.[3]

Award Suitability

The Best Research Article Award is intended, by its title, to recognize scholarly articles demonstrating research value and scientific contribution. For computational biology submissions, relevant evaluation considerations may include originality, research design, analytical rigor, data quality, reproducibility, clarity of presentation, and significance to biological research. The supplied profile provides identifying information and bibliometric context but does not specify a nominated article or provide official confirmation of an award decision. Eligibility and suitability should therefore be determined from the actual submission and the award organizer’s published criteria. [2]

Conclusion

This article provides a structured academic profile for Huseyin Cimen using the researcher details and bibliometric figures supplied. The profile connects the stated subject area of omics data analysis with the wider role of computational methods in biological research. Publication-level evidence remains necessary to establish specific research contributions and assess the suitability of an individual article for recognition. Verifying identifiers, current metrics, publication records, and official award information supports accurate and transparent academic communication. The article should be updated when authoritative publication records or confirmed award details become available.[3]

References

  1. Elsevier. (n.d.). Scopus author details: Huseyin Cimen, Author ID 35195463600.
    https://www.scopus.com/authid/detail.uri?authorId=35195463600
  2. Journal article. (2026.) Technofunctional Properties and Proteomic Profiling of Sesame Cake Protein Isolates Obtained by Green Extraction Methods and Treated with Cold Plasma.
    https://doi.org/10.3390/molecules31152638
  3. Computational Biologists Awards. (2026.). Official website.
    https://computationalbiologists.com/

Hedayat Hosseini | Metagenomics | Editorial Board Member

Published on by Computational Biologists

Editorial Board Member

Hedayat Hosseini
SMC Public Health Laboratory

Hedayat Hosseini
Affiliation SMC Public Health Laboratory
Country United States
Scopus ID 55445059500
Documents 285
Citations 10,425
h-index 28
Subject Area Metagenomics
Event Computational Biologists Awards

Hedayat Hosseini is identified in the supplied academic profile with SMC Public Health Laboratory in the United States, with metagenomics listed as the primary subject area. The provided Scopus metrics report 285 documents, 10,425 citations, and an h-index of 28. These indicators provide a quantitative overview of indexed scholarly activity, although they should be verified against the current author record before publication.[1]

Abstract

This academic profile presents Hedayat Hosseini, affiliated in the supplied information with SMC Public Health Laboratory in the United States, with metagenomics identified as the principal subject area. The reported Scopus metrics comprise 285 documents, 10,425 citations, and an h-index of 28. These indicators provide a bibliometric snapshot of indexed scholarly activity and offer context for examining research visibility. The article outlines the relevance of metagenomics to computational biology, describes broader research applications, and considers evidence appropriate for academic recognition through the Computational Biologists Awards. Specific research findings, editorial appointments, and award outcomes should be confirmed through authoritative records before being presented as established facts.[1]

Keywords

Hedayat Hosseini, Editorial Board Member, Metagenomics, Computational Biology, Public Health Laboratory, Bibliometrics, Research Evaluation, Computational Biologists Awards.[2]

Introduction

Metagenomics investigates genetic material recovered directly from environmental, clinical, and other complex samples, enabling analysis of microbial communities without requiring every organism to be cultured. Computational methods support sequence processing, taxonomic classification, functional annotation, and comparative analysis. These approaches connect genomics, bioinformatics, microbiology, and public health. Academic assessment in this field may consider methodological quality, reproducibility, publication records, and research relevance. The supplied Scopus author record provides a starting point for reviewing indexed activity, while individual contributions require confirmation through the original publications and associated institutional information.[1]

Research Profile

The supplied profile identifies Hedayat Hosseini with SMC Public Health Laboratory in the United States and lists metagenomics as the subject area. The reported bibliometric indicators are 285 documents, 10,425 citations, and an h-index of 28. These figures can help describe publication activity and citation visibility but do not independently establish research quality or the importance of particular findings. A comprehensive assessment should consider database coverage, publication types, author attribution, collaboration, and the date of retrieval. The current Scopus record should be consulted to verify these figures before they are relied upon in a formal academic assessment.[1]

Research Contributions

Metagenomics supports computational biology by enabling the investigation of microbial diversity, community composition, and functional potential using sequencing and computational analysis. Applications across the field include microbial surveillance, pathogen discovery, environmental monitoring, and characterization of complex biological populations. Contributions may involve reproducible bioinformatics pipelines, validated analytical workflows, robust statistical methods, and well-documented genomic datasets. These are general applications of metagenomics rather than verified claims about the individual’s research. Specific contributions attributable to Hedayat Hosseini should be established by reviewing the relevant original publications, author statements, and supporting research documentation.[3]

Publications

The supplied Scopus profile reports 285 documents associated with author identifier 55445059500. This figure offers an overview of indexed publication activity but does not provide a verified bibliography or establish the nature of each record. A publication-level review should examine article titles, author lists, journal or conference details, abstracts, publication dates, and persistent identifiers such as digital object identifiers. Original research should be distinguished from reviews, conference papers, corrections, and other indexed materials. The Scopus author profile provides a direct starting point for locating records and checking their attribution.[1]

Research Impact

The supplied citation count of 10,425 and h-index of 28 indicate measurable citation activity in the reported Scopus record. An h-index of 28 means that at least 28 publications have each received at least 28 citations, provided that the profile attribution and metrics are accurate at the time of measurement. Citation counts can vary between databases and change over time. They are best interpreted alongside originality, methodological reliability, independent use of findings, collaboration, and documented scientific or public health outcomes. Bibliometric measures should inform rather than replace qualitative assessment of research contributions.[1]

Award Suitability

The Computational Biologists Awards provide a context for recognizing research relevant to computational biology and related disciplines. The supplied profile offers bibliometric indicators and a metagenomics subject designation that may inform an initial review. A fair assessment should additionally examine publication relevance, originality, research integrity, reproducibility, professional service, and alignment with the published award criteria. Citation indicators alone cannot establish eligibility, confirm an editorial-board appointment, or determine an award outcome. Any formal claim of appointment or recognition should be supported by an official announcement or documentary record from the relevant organization.[2]

Conclusion

The supplied information identifies Hedayat Hosseini with SMC Public Health Laboratory in the United States and lists metagenomics as the principal subject area. The reported Scopus metrics offer a quantitative snapshot of indexed scholarly activity, while further review is needed to establish specific research contributions and their significance. A comprehensive academic assessment should combine verified publication records, scientific relevance, methodological quality, and documented professional service. Before publication, the bibliometric figures, affiliation, editorial role, and award-related statements should be checked against authoritative records to ensure accuracy and transparency.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Hedayat Hosseini, Author ID 55445059500.
    https://www.scopus.com/authid/detail.uri?authorId=55445059500
  2. Computational Biologists Awards. (2026.). Official website.
    https://computationalbiologists.com/
  3. Review Article. (2026.) Methods for Controlling Biogenic Amine Formation in Seafood: Ensuring Safety and Quality.
    https://doi.org/10.1016/j.jfp.2026.100892

Hadi Poormohammadi | Bioinformatics | Editorial Board Member

Published on by Computational Biologists

Editorial Board Member

Hadi Poormohammadi
Meybod University

Researcher profile
Name Hadi Poormohammadi
Affiliation Meybod University
Country Iran
Scopus ID 22836317200
Documents 9
Citations 48
h-index 4
Subject Area Bioinformatics
Event Computational Biologists Awards

Hadi Poormohammadi is identified in the supplied academic profile as a researcher affiliated with Meybod University in Iran, with bioinformatics listed as his subject area. His scholarly profile is associated with Scopus author identifier 22836317200. The provided bibliometric information reports nine documents, 48 citations and an h-index of four. These indicators offer a quantitative overview of the indexed publication and citation record, although they do not independently establish research quality or practical influence. This article presents the available profile information in the context of the Computational Biologists Awards without implying a verified editorial appointment or award outcome. [1]

Abstract

This article presents a scholarly profile of Hadi Poormohammadi, affiliated with Meybod University in Iran, whose listed subject area is bioinformatics. The supplied Scopus record identifies the researcher through author ID 22836317200 and reports nine documents, 48 citations and an h-index of four. These bibliometric indicators provide a concise overview of indexed research output and citation activity, although they do not independently establish research quality, originality or practical influence. The profile is presented in relation to the Computational Biologists Awards as a research-recognition context. Further assessment requires examination of publications, methodological contributions, authorship and independently verifiable professional information.[3]

Keywords

Hadi Poormohammadi; bioinformatics; computational biology; Meybod University; Scopus author profile; bibliometrics; scholarly publications; citation analysis; research recognition; Computational Biologists Awards.[1]

Introduction

Bioinformatics combines computational methods, statistical analysis and biological knowledge to investigate complex biological data. It supports research involving biological sequences, molecular interactions, genomic information and data-driven interpretation. Scholarly profiles help readers identify researchers and explore their indexed publications, while bibliometric indicators provide quantitative context for research activity. The supplied Scopus author record for Hadi Poormohammadi provides a starting point for locating publications associated with his author identifier. Interpretation of this record should take account of database coverage, the date of retrieval and the accuracy of author attribution. [1]

Research Profile

The supplied information identifies Hadi Poormohammadi as affiliated with Meybod University in Iran and associates his profile with bioinformatics. His Scopus author identifier is 22836317200. The reported record comprises nine documents, 48 citations and an h-index of four. These values should be interpreted as profile-specific bibliometric information rather than comprehensive measures of expertise, research quality or academic standing. Verification of institutional affiliation, publication authorship and current metrics should be undertaken through authoritative academic and bibliographic records before the profile is used for formal assessment. [1]

Research Contributions

Bioinformatics research may contribute to biological discovery through computational modelling, sequence analysis, data integration and the interpretation of complex molecular datasets. The nature and significance of an individual researcher’s contributions must be established from their publications, methods, datasets and documented findings. Although the supplied profile identifies bioinformatics as the subject area, publication titles and detailed research findings were not provided for this article. Specific discoveries, software outputs or methodological advances are therefore not attributed to Poormohammadi without supporting evidence. A reliable evaluation would examine the originality, reproducibility and scientific relevance of documented work.[3]

Publications

The supplied bibliometric information reports nine indexed documents associated with the researcher’s Scopus profile. A complete publication bibliography requires checking each record for its title, author list, publication venue, year and persistent identifier. Because individual publication details and verified digital object identifiers were not supplied, no specific paper or DOI is attributed to the researcher here. The Scopus author profile provides a starting point for reviewing indexed records and confirming publication metadata. Individual works should be checked against publisher records to establish accurate citations and distinguish publications by researchers with similar names. [1]

Research Impact

The reported 48 citations indicate citation activity within the indexed records represented by the supplied data. An h-index of four means that, according to the relevant database calculation, at least four publications have each received four or more citations. These indicators can assist preliminary assessment but are affected by publication coverage, disciplinary citation practices, co-authorship and the date of retrieval. A balanced evaluation should also consider reproducibility, methodological rigour, collaboration, research usefulness and the significance of individual findings. Citation counts alone cannot establish the broader scientific or societal impact of a researcher’s work. [1] [3]

Award Suitability

The Computational Biologists Awards provide a context for presenting research profiles associated with computational biology and related scientific disciplines. The supplied information identifies bioinformatics as the subject area and provides bibliometric indicators that may support an initial review. A formal assessment for an award or editorial-board appointment would require evidence of relevant research contributions, publication quality, professional service and compliance with the event’s applicable criteria. The profile alone does not establish eligibility, selection or appointment. Inclusion in this article should not be interpreted as confirmation that the researcher has received an award or holds an editorial-board position.[3]

Conclusion

The supplied academic profile identifies Hadi Poormohammadi as affiliated with Meybod University in Iran, with bioinformatics listed as his subject area. The reported Scopus indicators offer a concise snapshot of indexed publication and citation activity. These details provide a starting point for scholarly discovery but do not replace examination of individual publications, research methods or documented contributions. Further verification through authoritative academic and bibliographic records is necessary before drawing conclusions about research achievements, editorial responsibilities or award status. This distinction supports transparent and evidence-based academic recognition.[3]

References

  1. Elsevier. (n.d.). Scopus author details: Hadi Poormohammadi, Author ID 22836317200. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=22836317200
  2. Computational Biologists Awards. (n.d.). Official website.
    https://computationalbiologists.com/
  3. Journal Article. (2026. ) A novel deep learning approach for mosquito species classification via a dual-head structure and calibration-aware fusion architecture.
    https://doi.org/10.1038/s41598-026-35453-1

Fatemeh Moosavi | Molecular Dynamics Simulations | Editorial-Board-Member

Published on by Computational Biologists

“`

Editorial Board Member

Fatemeh Moosavi

Researcher associated with Ferdowsi University of Mashhad

Fatemeh Moosavi
Affiliation Ferdowsi University of Mashhad
Country Iran
Scopus ID 56598607700
Documents 85
Citations 1,508
h-index 10
Subject Area Molecular Dynamics Simulations
Event Computational Biologists Awards
ORCID 0000-0001-9676-5881

Fatemeh Moosavi is identified in the supplied researcher information as being affiliated with Ferdowsi University of Mashhad in Iran, with molecular dynamics simulations listed as a subject area. The provided bibliometric figures report 85 documents, 1,508 citations and an h-index of 10. These indicators provide a preliminary overview of reported research output and citation activity. The linked Scopus author profile and ORCID record offer starting points for checking publication metadata and researcher identification. Editorial-board membership and award-related eligibility should be verified through official documentation before being presented as confirmed appointments or achievements.[1]

Abstract

This article presents an academic profile of Fatemeh Moosavi, whose supplied researcher details identify an affiliation with Ferdowsi University of Mashhad, Iran, and an interest area in molecular dynamics simulations. The provided bibliometric information lists 85 documents, 1,508 citations and an h-index of 10. These indicators offer a preliminary quantitative snapshot of reported research output and citation activity, subject to confirmation against current database records. The profile also provides links to Scopus, ORCID and the Computational Biologists Awards website. Publication details, editorial appointments and award eligibility require verification before being stated as independently established facts.[2]

Keywords

Fatemeh Moosavi; Ferdowsi University of Mashhad; Iran; molecular dynamics simulations; computational biology; research publications; citation analysis; Scopus; ORCID; academic profile; research recognition; bibliometrics.[1]

Introduction

Academic researcher profiles bring together institutional affiliations, publications, identifiers and citation indicators to support the discovery and evaluation of scholarly work. Scopus author records and ORCID profiles can help readers distinguish researchers, inspect publication histories and identify related research outputs. However, profiles may differ in coverage, indexing and update frequency. The information presented here is based on the supplied details and linked profile endpoints; it should be checked against the original records before being used for formal appointments, award decisions or institutional reporting.[1][2]

Research Profile

The supplied profile identifies Fatemeh Moosavi with Ferdowsi University of Mashhad in Iran and lists molecular dynamics simulations as the subject area. Molecular dynamics is a computational method used to investigate the time-dependent behaviour of interacting atoms and molecules. Depending on the research question, it can contribute to studies of molecular structure, interactions and dynamic processes. Specific research themes, laboratory responsibilities, academic rank and current institutional position are not independently established by the information provided and should be confirmed through official institutional or publication records.[2]

Research Contributions

Molecular dynamics simulations provide a computational framework for studying molecular motion and interactions under defined model conditions. Their scientific value depends on appropriate model selection, parameterisation, sampling, validation and interpretation alongside relevant experimental or theoretical evidence. A researcher’s contributions in this area are best assessed by examining individual publications, methodological details, reproducibility and relevance to the scientific question. The available input does not identify particular studies or establish specific discoveries attributable to Fatemeh Moosavi; individual contributions should therefore be described only after the underlying publications have been verified.[1]

Publications

The supplied bibliometric summary reports 85 documents associated with the researcher. This figure should be checked against the linked Scopus record because indexed document totals may change as databases are updated, records are merged and author attribution is corrected. A complete publication review would examine article titles, author lists, journal or conference information, publication years and persistent identifiers, including DOIs where available. No individual paper titles or DOI identifiers were supplied for this profile, so specific publications cannot be listed reliably without further verification.[1]

Research Impact

The provided figures report 1,508 citations and an h-index of 10. Citation counts describe recorded references to indexed research, while the h-index combines publication productivity and citation distribution into a single indicator. Neither measure alone establishes research quality, originality or societal impact. Interpretation should account for subject-area citation practices, publication age, database coverage and author disambiguation. Because these figures were supplied as input rather than independently retrieved from a live database, they are presented as reported values and should be rechecked before formal publication or evaluation.[1]

Award Suitability

The Computational Biologists Awards website is provided as the relevant event link. A documented assessment of suitability for an award or editorial-board position should consider the official eligibility criteria, verified publications, research relevance, professional experience and evidence of editorial service. The bibliometric figures supplied may form part of a broader review, but they do not by themselves establish eligibility, selection or appointment. No confirmed award result or editorial-board appointment is asserted in this article. Readers should consult the event’s official information and request documentary confirmation where necessary.[3]

Conclusion

The supplied information outlines a researcher profile associated with Ferdowsi University of Mashhad, Iran, with molecular dynamics simulations identified as the subject area. Reported bibliometric indicators provide a preliminary overview, while the linked Scopus and ORCID records offer routes for further examination. A reliable academic assessment should verify the current affiliation, publication list, citation statistics and any claimed editorial or award status using authoritative records. This page is a structured profile based on the provided input, not an independent certification of academic credentials or recognition.[2]

References

  1. Elsevier. (n.d.). Scopus author details: Fatemeh Moosavi, Author ID 56598607700.
    https://www.scopus.com/authid/detail.uri?authorId=56598607700
  2. ORCID. (n.d.). ORCID record: 0000-0001-9676-5881. ORCID
    https://orcid.org/0000-0001-9676-5881
  3. Computational Biologists Awards. (2026.). Official award website.
    https://computationalbiologists.com/
  4. Journal article. (2026.). Comprehensive study on the structure and dynamics of ammonium-based biocompatible ionic liquids .
    https://doi.org/10.1039/d5cp04596g
  5. Journal article. (2026.).Dopamine Interaction with Dna/Rna Aptamers: Molecular Dynamics Simulation.
    http://dx.doi.org/10.2139/ssrn.4767051

Vahid Akmali | Computational Phylogenetics | Editorial Board Member

Published on by Computational Biologists

 

Editorial Board Member

Vahid Akmali
Razi University

Vahid Akmali
Affiliation Razi University
Country Iran
Scopus ID 54978642800
Documents 47
Citations 362
h-index 12
Subject area Computational Phylogenetics
Event Computational Biologists Awards
ORCID 0000-0001-8946-3527

Vahid Akmali is a researcher affiliated with Razi University in Iran whose supplied bibliometric profile identifies computational phylogenetics as his subject area. His publication record is reported as 47 documents, 362 citations, and an h-index of 12. These indicators provide a quantitative overview of the indexed research output and citation activity associated with the supplied Scopus author identifier. This article presents a structured overview of his research profile, the relevance of computational phylogenetics, and the potential relationship between his academic background and editorial or research recognition within the Computational Biologists Awards. [1]

Abstract

This article presents an academic profile of Vahid Akmali, affiliated with Razi University in Iran, with a stated research focus in computational phylogenetics. The supplied bibliometric information records 47 documents, 362 citations, and an h-index of 12 under Scopus author identifier 54978642800. His profile is considered in the context of computational biology, where computational and statistical methods support the analysis of evolutionary relationships and biological data. The article outlines the subject area’s significance, discusses publication and citation indicators, and considers potential relevance to editorial service and research recognition through the Computational Biologists Awards. Profile details should be interpreted alongside verified publications and institutional records.[2]

Keywords

Vahid Akmali; computational phylogenetics; computational biology; evolutionary analysis; phylogenetic inference; bioinformatics; research metrics; scientific publications; citation analysis; Razi University; editorial board; Computational Biologists Awards.[1]

Introduction

Computational biology combines computational techniques, mathematical modelling, and biological knowledge to investigate complex questions about living systems. Computational phylogenetics is an important area within this discipline because it uses biological data and analytical methods to infer evolutionary relationships among organisms, genes, or other biological entities. These methods can support comparative studies, evolutionary research, and the interpretation of molecular datasets. [2]

Research Profile

The supplied profile identifies Vahid Akmali with Razi University in Iran and lists computational phylogenetics as his subject area. His reported Scopus indicators comprise 47 documents, 362 citations, and an h-index of 12. These figures offer a snapshot of indexed scholarly output and citation activity, although they do not independently establish the quality, originality, or practical significance of individual studies. A comprehensive assessment would examine his verified publication titles, research questions, methods, co-authorship, and contributions to the development or application of computational approaches in biological research. [1]

Research Contributions

Computational phylogenetics draws on algorithms, evolutionary models, and sequence-based analyses to reconstruct relationships and investigate patterns of biological diversification. Work in this area may involve assessing alternative phylogenetic trees, comparing evolutionary hypotheses, evaluating model assumptions, and interpreting uncertainty in inferred relationships. These activities can contribute to broader research in genomics, molecular evolution, biodiversity, and comparative biology. The available profile information establishes a subject-area association but does not identify specific methods, discoveries, or publications attributable to Akmali; such contributions should therefore be described only after examining primary scholarly records.[2]

Publications

The supplied Scopus profile reports 47 documents associated with author identifier 54978642800. This document count provides a starting point for reviewing the researcher’s publication history, but it should not be treated as a verified list of individual works without consulting the author record. A publication-level review should confirm titles, co-authors, journal or conference details, publication dates, and persistent identifiers such as digital object identifiers (DOIs). No specific publication titles or DOI records have been supplied for this article, so individual papers are not listed here. [1]

Research Impact

The reported total of 362 citations and h-index of 12 offers a quantitative indication of the citation activity associated with the supplied Scopus profile. An h-index of 12 conventionally indicates that at least 12 indexed publications have each received at least 12 citations, provided that the underlying record and metric are accurate. Citation counts vary between databases and change over time, and they may be influenced by research-field practices, publication age, collaboration patterns, and database coverage. Accordingly, these metrics are best considered alongside qualitative assessments of methodological rigour, reproducibility, relevance, and documented scholarly contributions.[2]

Award Suitability

The Computational Biologists Awards provide a context for recognizing research and professional contributions related to computational biology. Akmali’s stated subject area and reported bibliometric indicators may be relevant to an initial profile review. However, the available information does not establish a confirmed award nomination, selection, or editorial appointment. A fair assessment of suitability would require verified publications, evidence of original contributions, documented professional service where applicable, and alignment with the relevant award criteria. Any recognition or editorial role should be presented as confirmed only when supported by an official announcement or reliable institutional documentation.[1]

Conclusion

Vahid Akmali’s supplied academic profile connects his affiliation with Razi University to the research area of computational phylogenetics. The reported 47 documents, 362 citations, and h-index of 12 provide a concise bibliometric overview, while the broader significance of his work requires examination of verified publications and their scientific contributions. Computational phylogenetics remains an important component of computational biology because it supports the study of evolutionary relationships through analytical methods. Maintaining accurate author identifiers, publication records, and independently verified information is essential when presenting researchers in academic profiles and award-related materials.[2]

References

  1. Elsevier. (n.d.). Scopus author details: Vahid Akmali, Author ID 54978642800. Scopus. Author metrics and profile details should be checked against the live record.
    https://www.scopus.com/authid/detail.uri?authorId=54978642800
  2. Journal article(2023.)An Introduction to the Comparison Shape of some Cranial Structures in Boleophthalmus Dussumieri and Periophthalmus Waltoni (Teleostei: Oxudercidae) in the Persian Gulf: An Exploratory Analysis with Micro-CT Scanning
    https://doi.org/10.18502/fbt.v11i1.14510
  3. ORCID. (n.d.). Vahid Akmali researcher identifier. ORCID. 
    https://orcid.org/0000-0001-8946-3527

Essam Houssein | Computational Neuroscience | Innovative Research Award

Published on by Computational Biologists

Innovative Research Award

Essam Houssein
Minia University

Essam Houssein
Affiliation Minia University
Country Egypt
Scopus ID 43361385400
Documents 324
Citations 18,566
h-index 70
Subject area Computational Neuroscience
Event Computational Biologists Awards
ORCID 0000-0002-8127-7233

Essam Houssein is a researcher affiliated with Minia University in Egypt. His research profile is presented in the context of computational neuroscience, a field that applies computational methods and mathematical models to investigate neural systems and brain function. The Innovative Research Award recognizes research contributions that demonstrate originality, methodological development, and potential scientific value. This article summarizes the supplied researcher information, outlines the relevance of computational approaches to neuroscience, and describes the scholarly considerations associated with research recognition through the Computational Biologists Awards. Bibliometric figures should be checked against current source records.[1]

Abstract

This article presents the research profile of Essam Houssein, affiliated with Minia University, Egypt, and identifies computational neuroscience as the subject area associated with this recognition profile. The supplied Scopus metrics list 324 documents, 18,566 citations, and an h-index of 70. These indicators offer quantitative perspectives on publication activity and scholarly attention, although they do not independently establish research quality or originality. The Innovative Research Award provides a framework for recognizing contributions to scientific progress. Assessment of research innovation should consider methodological rigor, reproducibility, originality, practical relevance, and the significance of individual contributions within the broader research community..[3]

Keywords

Essam Houssein; Innovative Research Award; Computational Neuroscience; Minia University; Egypt; scientific innovation; bibliometrics; computational modeling; neural systems; research impact; scholarly communication; Computational Biologists Awards.[1]

Introduction

Computational neuroscience combines neuroscience with mathematical analysis, statistics, computer science, and computational modeling to investigate how nervous systems process information. Its methods can help researchers formulate hypotheses, analyze complex observations, and study mechanisms that are difficult to examine through experimental approaches alone. Computational research increasingly supports interdisciplinary collaboration across biological and quantitative sciences. Recognition in this area should reflect documented contributions, sound methodology, and scientific relevance. The supplied profile of Essam Houssein provides bibliometric context for an academic recognition article, while the researcher’s publications and source records remain the appropriate basis for evaluating specific scientific achievements.[1]

Research Profile

The information supplied for this profile identifies Essam Houssein with Minia University in Egypt and provides a Scopus Author ID of 43361385400. The associated bibliometric figures are 324 documents, 18,566 citations, and an h-index of 70. These numbers are reported as supplied and may change as indexing databases are updated. Institutional affiliation, author identity, publication attribution, and research subject classification should be confirmed against the corresponding authoritative records before this article is used for formal evaluation or institutional publication.[1]

Research Contributions

Research contributions in computational neuroscience may include the development of mathematical models, computational algorithms, statistical techniques, neural data-analysis pipelines, and reproducible methods for interpreting biological signals. Their scientific value depends on the clarity of the research question, the suitability of the methods, validation against appropriate evidence, and the extent to which results advance understanding. The supplied information does not identify individual publications or specific methods attributable to Essam Houssein. Accordingly, particular discoveries or technical innovations should not be assigned to the researcher without verification from relevant publications and institutional or bibliographic records.[2]

Publications

The supplied Scopus profile reports 324 documents associated with the researcher. A publication-level review is necessary to establish the titles, publication venues, authorship roles, research topics, and dates represented by this record. Publication counts can provide an overview of scholarly output, but they do not distinguish between article types, research significance, or individual contributions to collaborative work. A verified publication list should be retrieved from the author’s bibliographic profile and cross-checked against publisher records. No individual paper titles or DOI identifiers are asserted here because a verified publication list was not included in the supplied data. [1]

Research Impact

The supplied citation total of 18,566 and h-index of 70 describe aspects of the research profile’s indexed citation record. The h-index combines publication productivity with citation frequency by counting a set of papers that have each received at least the corresponding number of citations. Such indicators are influenced by disciplinary practices, publication age, collaboration patterns, database coverage, and citation behavior. They are best interpreted alongside qualitative assessment of originality, methodological reliability, research transparency, and contribution to scientific knowledge rather than used as standalone measures of research excellence.[3]

Award Suitability

The Innovative Research Award is intended, in this article’s recognition context, to highlight scientific work demonstrating originality, rigor, and potential value to a research field. The supplied publication and citation metrics offer quantitative background for reviewing Essam Houssein’s academic profile, but award suitability should be determined through evidence-based evaluation of actual research outputs. Relevant considerations include methodological innovation, documented research contributions, publication quality, and potential influence on future studies. The event’s formal eligibility requirements and judging criteria should be consulted before presenting this profile as confirmation of an award decision.[1]

Conclusion

The supplied profile identifies Essam Houssein as a researcher affiliated with Minia University in Egypt and reports a Scopus record of 324 documents, 18,566 citations, and an h-index of 70. Computational neuroscience offers an interdisciplinary setting in which computational methods contribute to the investigation of neural systems and biological information processing. These bibliometric indicators provide context rather than a complete assessment of scientific achievement. A robust academic recognition profile should combine verified researcher identity, publication-level evidence, documented contributions, and transparent evaluation criteria. Current source records should be consulted before the information is used in formal award materials..[3]

References

  1. Elsevier. (n.d.). Scopus author details: Essam Houssein, Author ID 43361385400. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=43361385400
  2. Journal article. (2025). Integrated deep learning-based IRACE and convolutional neural networks for chest X-ray image classification.
    https://doi.org/10.1016/j.knosys.2025.114293
  3. Journal article. (2025). Computer-aided diagnosis system for predicting liver cancer disease using modified Genghis Khan Shark Optimizer algorithm.
    https://doi.org/10.1016/j.eswa.2025.128017
  4. Computational Biologists Awards. (2026. )  Computational Biologists Awards.
    https://computationalbiologists.com/
  5. ORCID. (n.d.). Essam Houssein: ORCID researcher identifier.
    https://orcid.org/0000-0002-8127-7233

Dong Soo Lee | Computational Genomics | Innovative Research Award

Published on by Computational Biologists

Innovative Research Award

Dong Soo Lee
College of Medicine, The Catholic University of Korea

Dong Soo Lee
Affiliation College of Medicine, The Catholic University of Korea
Country South Korea
Scopus ID 57811935400
Documents 56
Citations 841
h-index 19
Subject Area Computational Genomics
Event Computational Biologists Awards
ORCID 0000-0001-7880-8147

The Innovative Research Award recognizes research contributions that demonstrate originality, methodological rigor, and potential value to scientific knowledge. This article presents a research profile of Dong Soo Lee, affiliated with the College of Medicine, These indicators provide a quantitative overview of indexed scholarly output and citation activity, although they do not independently establish research quality or award eligibility. The profile contextualizes computational genomics within contemporary biomedical research and outlines considerations for evaluating innovation, reproducibility, and potential scientific impact.[1]

Abstract

Computational genomics applies computational methods to genomic information to investigate biological variation, molecular mechanisms, and relationships between genetic features and biological outcomes. This article summarizes the supplied research profile of Dong Soo Lee, whose institutional affiliation is the College of Medicine, The Catholic University of Korea, South Korea. The reported scholarly indicators comprise 56 documents, 841 citations, and an h-index of 19. These figures offer a descriptive perspective on publication and citation activity. The profile also considers the relevance of reproducible analysis, robust data interpretation, interdisciplinary collaboration, and transparent research methods when assessing scientific contributions and potential suitability for recognition through the Innovative Research Award.[1]

Keywords

Computational genomics; bioinformatics; genomic data analysis; biomedical research; statistical genetics; reproducible science; research innovation; bibliometrics; scientific collaboration; Innovative Research Award. [3]

Introduction

Computational genomics integrates computational biology, statistics, and genomic technologies to extract meaningful information from complex biological datasets. Its applications include sequence analysis, variant interpretation, gene regulation, and the investigation of molecular systems. Reliable findings depend on appropriate analytical methods, transparent reporting, and independent validation. Established bioinformatics literature emphasizes the importance of computational tools and reproducible workflows in modern biological research. [2] Within this context, research recognition should consider the originality and reliability of an individual’s documented contributions rather than relying exclusively on publication or citation totals.

Research Profile

Dong Soo Lee is identified in the supplied information as affiliated with the College of Medicine, The Catholic University of Korea, in South Korea. The stated subject area for this profile is computational genomics. The provided Scopus identifier is 57811935400, and the ORCID identifier is 0000-0001-7880-8147. These identifiers offer routes for locating researcher records and distinguishing scholarly profiles. The affiliation and subject-area details are presented as supplied and should be checked against current institutional and researcher records before formal publication. [1] [3]

Research Contributions

Contributions in computational genomics may include developing analytical pipelines, integrating heterogeneous genomic datasets, improving statistical interpretation, and applying computational techniques to biomedical questions. Such work can support the identification of biological patterns and the generation of testable hypotheses. Assessing an individual researcher’s contributions requires examining specific publications, methodological innovations, authorship roles, validation practices, and documented applications. General developments in genomic analysis provide the scientific context for this assessment, but they should not be attributed to a particular researcher without supporting publication-level evidence. [2] [4]

Publications

The supplied bibliometric summary reports 56 documents associated with the research profile. A publication-level assessment should verify article titles, publication venues, dates, author order, research methods, and relevance to computational genomics. The available input does not include a verified publication list, so individual papers, publication years, journal details, and digital object identifiers cannot be responsibly specified here. The linked Scopus author record is the appropriate starting point for reviewing indexed publications, subject classifications, and citation information. [1]

Research Impact

The reported 841 citations and h-index of 19 describe aspects of the supplied bibliometric profile. An h-index of 19 indicates that, under the dataset and counting method used, at least 19 indexed works have each received at least 19 citations. Citation counts may differ across databases and can change over time. They are influenced by field practices, publication age, collaboration, and database coverage, and should therefore be interpreted alongside research quality, methodological soundness, and demonstrated scientific or practical contributions. [1] [5]

Award Suitability

The Innovative Research Award of the Computational Biologists Awards provides a recognition context for evaluating originality, research rigor, and contributions to scientific advancement. The supplied publication and citation indicators may serve as background information during an assessment, but they are insufficient to establish award eligibility or confirm a selection outcome. A balanced review should examine the candidate’s verified research outputs, originality, reproducibility, individual contributions, relevance to computational biology, and potential scientific impact. Final suitability should be determined by the award committee using its published criteria and independently verifiable evidence.

Conclusion

The supplied information identifies Dong Soo Lee with the College of Medicine, The Catholic University of Korea, and a stated research focus in computational genomics. The reported metrics of 56 documents, 841 citations, and an h-index of 19 provide a concise bibliometric overview, subject to verification against current database records. A rigorous account of research achievement should also document individual publications, methodological contributions, reproducibility, and evidence of scientific influence. These elements provide a stronger basis for evaluating research innovation than quantitative indicators alone and support a transparent approach to academic recognition.

References

  1. Elsevier. (n.d.). Scopus author details: Dong Soo Lee, Author ID 57811935400. Scopus. Researcher metrics and publication information should be verified against the current record.
    https://www.scopus.com/authid/detail.uri?authorId=57811935400
  2. Journal article (2026. ) Prediction of Tumor Complete Response Using Genomic and Clinical Data in Solid Cancer Undergoing Definitive Radiation Therapy.
    https://doi.org/10.3390/ijms27208991
  3. ORCID. (n.d.). Dong Soo Lee: ORCID researcher record. ORCID.
    https://orcid.org/0000-0001-7880-8147
  4. Journal article (2023. ) Association between gut microbial change and acute gastrointestinal toxicity in patients with prostate cancer receiving definitive radiation therapy.
    https://doi.org/10.1002/cam4.6636
  5. Computational Biologists Awards. (2026. )  Computational Biologists Awards.
    https://computationalbiologists.com/

Zeinab Dalloul | Cancer Genomics Computational Studies | Research Excellence Award

Published on by Computational Biologists

Research Excellence Award

Zeinab Dalloul
Algentics

Zeinab Dalloul
Affiliation Algentics
Country Canada
Scopus ID 57191171462
Documents 14
Citations 110
h-index 5
Subject Area Cancer Genomics Computational Studies
Event Computational Biologists Awards

Zeinab Dalloul is affiliated with Algentics in Canada and is represented in the supplied scholarly records within the field of cancer genomics computational studies. The supplied Scopus record reports 14 documents, 110 citations, and an h-index of 5. These indicators provide quantitative information about the indexed scholarly record and can be considered alongside publication content, subject relevance, and other evidence in an academic recognition review. [1]

Abstract

Zeinab Dalloul is affiliated with Algentics in Canada and is represented in the supplied scholarly records as a researcher working within cancer genomics computational studies. Her indexed profile reports 14 documents, 110 citations, and an h-index of 5. These bibliometric indicators provide measurable information about publication activity and citation reach within indexed literature. Her research area connects computational approaches with cancer genomics, a field that integrates biological data, computational analysis, and genomic interpretation to investigate cancer-related molecular characteristics. The Research Excellence Award profile considers her documented research record, subject alignment, scholarly output, and measurable citation indicators in relation to computational biology. [1]

Keywords

Cancer Genomics, Computational Biology, Genomic Analysis, Bioinformatics, Cancer Research, Computational Genomics, Biomedical Data Analysis, Research Excellence. [1]

Introduction

Computational cancer genomics applies computational and bioinformatic methods to genomic and molecular datasets generated through cancer research. Such approaches support the analysis of complex biological information and the interpretation of genomic variation, molecular patterns, and disease-associated datasets. Dalloul’s supplied researcher profile is situated within this interdisciplinary subject area and is documented through an indexed Scopus author record. [1]

Research Profile

Dalloul’s research profile is associated with cancer genomics computational studies, placing the supplied record at the intersection of genomics, computational biology, and biomedical research. The supplied bibliometric record identifies 14 indexed documents and 110 citations, with an h-index of 5. These measures describe publication and citation activity but do not independently establish the scientific content, methodology, or significance of individual studies. [1]

Research Contributions

Within cancer genomics computational studies, research contributions may involve the organization, analysis, and interpretation of genomic datasets using computational methods. Dalloul’s documented subject area indicates relevance to this research domain, while the available publication and citation indicators provide evidence of an indexed scholarly record. Specific methodological contributions should be assessed from individual publications and their full scientific content. [1]

Publications

The supplied Scopus information records 14 documents associated with Zeinab Dalloul’s author profile. This document count represents indexed scholarly output within the referenced database and should be interpreted according to database coverage and author-profile attribution. Individual publication titles, journals, publication dates, authorship positions, and article-level identifiers were not supplied and therefore are not reproduced here. [1]

Research Impact

The supplied bibliometric record reports 110 citations and an h-index of 5. Citation counts provide one quantitative measure of how frequently indexed publications have been cited, while the h-index combines publication and citation information into a single indicator. Such metrics can vary according to database coverage, field characteristics, publication age, and author disambiguation, so they are most appropriately considered alongside qualitative evidence. [1]

Award Suitability

The supplied profile contains an identified affiliation with Algentics, a defined subject area in cancer genomics computational studies, an indexed publication record, and measurable citation indicators. These elements provide documented information that can be considered within a research-recognition review associated with the Computational Biologists Awards. Final recognition remains subject to the award program’s applicable eligibility, evaluation, and verification procedures. [3]

Conclusion

Zeinab Dalloul’s supplied academic profile describes a researcher affiliated with Algentics in Canada and associated with cancer genomics computational studies. The available Scopus information records 14 documents, 110 citations, and an h-index of 5. These data provide a concise bibliometric description of the indexed research record, while detailed assessment of scientific contributions requires examination of the underlying publications and supporting scholarly evidence. [1] [2]

References

  1. Elsevier. (n.d.). Scopus author details: Zeinab Dalloul, Author ID 57191171462. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57191171462
  2. Review article. (2025.) Leveraging liquid biopsy to uncover resistance mechanisms and guide personalized immunotherapy.
    https://doi.org/10.1016/j.tranon.2025.102445
  3. Computational Biologists Awards. (2026. )  Computational Biologists Awards.
    https://computationalbiologists.com/