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/

Mingxiong He | Omics Data Analysis | Innovative Research Award

Published on by Computational Biologists

Innovative Research Award

Mingxiong He
Biogas Iinstitute of Ministry of Agriculture and Rural Affairs

Mingxiong He
Affiliation Biogas Iinstitute of Ministry of Agriculture and Rural Affairs
Country China
Scopus ID 18436995800
Documents 133
Citations 4,058
h-index 34
Subject Area Omics Data Analysis
Event Computational Biologists Awards
ORCID 0000-0002-9780-6865

Mingxiong He is a researcher associated with the Biogas Iinstitute of Ministry of Agriculture and Rural Affairs in China. The supplied research profile identifies Omics Data Analysis as the principal subject area and records 133 documents, 4,058 citations, and an h-index of 34 in Scopus. These bibliometric indicators provide a quantitative description of publication activity and citation impact and should be interpreted in relation to field, publication age, collaboration patterns, and database coverage. [1]

Abstract

Mingxiong He is identified in the supplied academic profile as a researcher working in Omics Data Analysis at the Biogas Iinstitute of Ministry of Agriculture and Rural Affairs, China. The profile reports 133 Scopus-indexed documents, 4,058 citations, and an h-index of 34. These indicators describe a substantial body of indexed scholarly output and accumulated citation activity. Omics data analysis integrates computational methods with large-scale biological datasets to characterize molecular patterns and relationships. Such approaches can support genomics, transcriptomics, systems biology, and related research areas. The profile provides a basis for documenting research activity and considering eligibility for recognition through the Computational Biologists Awards.

Keywords

Mingxiong He, Innovative Research Award, Omics Data Analysis, computational biology, bioinformatics, biological data analysis, genomics, molecular data, research impact, Scopus, scholarly publications, Computational Biologists Awards.

Introduction

Omics research generates large and complex datasets that require computational approaches for organization, statistical analysis, interpretation, and biological discovery. Modern multi-omics studies may integrate genomic, transcriptomic, proteomic, metabolomic, and other molecular measurements to investigate biological systems from complementary perspectives. [3] Within this context, computational biology provides methods for transforming high-dimensional biological observations into interpretable research findings.

Research Profile

The supplied Scopus profile records 133 documents, 4,058 citations, and an h-index of 34 for Mingxiong He. The h-index is a bibliometric measure intended to combine publication productivity with citation frequency, while total citation counts reflect accumulated citations across indexed documents. Such metrics are database-dependent and can change over time as new publications and citations are indexed. [1]

Research Contributions

Research contributions within Omics Data Analysis can encompass computational methodology, biological data processing, statistical interpretation, molecular profiling, and integration of heterogeneous datasets. Multi-omics approaches are increasingly used to examine biological processes through complementary molecular layers, allowing researchers to investigate relationships that may not be apparent from a single data type. [3] The supplied profile supports describing Mingxiong He as a researcher working within this computational and data-intensive research environment.

Publications

In omics-oriented research, publications may involve sequencing technologies, molecular profiling, computational pipelines, statistical analysis, or integration of multiple biological datasets. RNA-sequencing analysis illustrates the breadth of computational procedures required to convert sequencing data into biologically interpretable results. [4] The specific publication topics attributable to Mingxiong He should be verified directly through the researcher’s indexed author record and associated publication records.

Research Impact

The supplied profile reports 4,058 citations and an h-index of 34. These measures indicate accumulated citation activity within the indexed research record, but bibliometric indicators should be interpreted alongside disciplinary norms, career duration, collaboration patterns, publication types, and database coverage. [1]

Award Suitability

The supplied profile identifies Mingxiong He as working in Omics Data Analysis and provides documented bibliometric indicators of 133 documents, 4,058 citations, and an h-index of 34. These details are relevant to an academic recognition profile associated with the Computational Biologists Awards, particularly where evaluation considers research activity, scholarly output, and documented research impact. [1]

Conclusion

Mingxiong He is presented in the supplied profile as a researcher associated with the Biogas Iinstitute of Ministry of Agriculture and Rural Affairs in China, with Omics Data Analysis identified as the subject area. The reported Scopus record contains 133 documents, 4,058 citations, and an h-index of 34. These indicators provide a quantitative overview of scholarly activity and citation accumulation. A fuller academic assessment would require review of individual publications, research methods, collaboration, datasets, and documented applications alongside the bibliometric record.

References

  1. Elsevier. (n.d.). Scopus author details: Mingxiong He, Author ID 18436995800. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=18436995800
  2. ORCID. (n.d.). ORCID record: Mingxiong He, ORCID iD 0000-0002-9780-6865.
    https://orcid.org/0000-0002-9780-6865
  3. Journal article (2017. )  Acinetobacter larvae sp. nov., isolated from the larval gut of omphisa fuscidentalis.
    https://doi.org/10.1099/ijsem.0.001644
  4. Journal article (2017. ) Bio-ethanol production by Zymomonas mobilis using pretreated dairy manure as a carbon and nitrogen source.
    https://doi.org/10.1039/c6ra26288k
  5. Computational Biologists Awards. (2026. ) Computational Biologists Awards official website.
    https://computationalbiologists.com/

Jin-Ji Yang | Pulmonary oncology | Personalized Medicine Innovation

Published on by Computational Biologists

Personalized Medicine Innovation

Jin-Ji Yang
Guangdong Provincial People’s Hospital

Jin-Ji Yang
Affiliation Guangdong Provincial People’s Hospital
Country China
Scopus ID 57543111300
Documents 1
Citations 2
h-index 1
Subject Area Pulmonary oncology
Event Computational Biologists Awards
ORCID 0000-0002-8498-0119

Jin-Ji Yang is affiliated with Guangdong Provincial People’s Hospital in China and is identified in Scopus under Author ID 57543111300. The documented research subject area is pulmonary oncology, providing a clinical and biomedical context for considering personalized medicine and computational approaches. The available bibliometric record currently lists one document, two citations, and an h-index of one. [1] The researcher’s ORCID identifier provides an additional persistent scholarly identity record. [2]

Abstract

Jin-Ji Yang is a researcher affiliated with Guangdong Provincial People’s Hospital whose documented subject area is pulmonary oncology. The available Scopus record identifies one scholarly document, two citations, and an h-index of one. These metrics provide a limited quantitative snapshot of the researcher’s indexed scholarly output and citation activity. [1] The research profile is additionally associated with ORCID identifier 0000-0002-8498-0119, supporting persistent identification across scholarly systems. [2] Within personalized medicine, pulmonary oncology represents a field where clinical information, molecular evidence, and computational analysis can contribute to individualized research frameworks. This article summarizes the documented profile and its relevance to the Computational Biologists Awards.

Keywords

Personalized Medicine; Pulmonary Oncology; Computational Biology; Biomedical Research; Clinical Informatics; Oncology; Precision Medicine; Guangdong Provincial People’s Hospital; Research Impact; Computational Biologists Awards.

Introduction

Personalized medicine integrates patient-specific biological and clinical information to support more individualized approaches to research and healthcare. Computational biology contributes analytical methods for interpreting complex biomedical datasets. Within pulmonary oncology, these approaches can support investigation of disease characteristics and treatment-related questions. Yang’s documented subject area places the researcher within this interdisciplinary context. [1]

Research Profile

Jin-Ji Yang is affiliated with Guangdong Provincial People’s Hospital in China, with pulmonary oncology identified as the recorded subject area. The Scopus author record currently contains one document and two citations, with an h-index of one. [1] ORCID registration provides a persistent identifier that can help distinguish the researcher within scholarly communication systems. [2]

Research Contributions

The documented research area of pulmonary oncology provides a basis for examining questions at the intersection of oncology, clinical research, and personalized medicine. Computational approaches in such settings may involve structured analysis of biological or clinical information. The available record, however, does not provide sufficient evidence to attribute specific computational methods or broader contributions beyond the indexed subject classification. [1]

Publications

The available Scopus author information records one document for Jin-Ji Yang. [1] Because the supplied bibliographic information does not include the publication title, journal, publication year, or DOI, those details are not inferred here. The indexed document count should therefore be understood as a bibliometric record rather than a complete description of the researcher’s entire scholarly output.

Research Impact

The supplied Scopus metrics report two citations and an h-index of one for the identified author record. [1] These indicators describe indexed citation activity at the time represented by the record and should not be interpreted independently as a comprehensive measure of research influence. Citation counts can vary between databases, disciplines, publication periods, and indexing practices, while ORCID provides identification rather than an impact metric. [2]

Award Suitability

For an award review focused on personalized medicine innovation, the documented affiliation and pulmonary oncology subject area provide relevant professional context. [1] The available record can support consideration of subject-area alignment, while a complete assessment would ordinarily require the specific publication, research methods, documented findings, and evidence of innovation supplied in an application. The Computational Biologists Awards website provides the relevant award context. [3]

Conclusion

Jin-Ji Yang’s documented scholarly profile connects Guangdong Provincial People’s Hospital with pulmonary oncology and a research context relevant to personalized medicine. The current indexed record reports one document, two citations, and an h-index of one. [1] ORCID further establishes a persistent researcher identifier. [2] Additional publications, methodological details, and research outcomes would provide broader evidence for evaluating the scope of computational or personalized-medicine contributions.

References

  1. Elsevier. (n.d.). Scopus author details: Jin-Ji Yang, Author ID 57543111300. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57543111300
  2. ORCID. (n.d.). Jin-Ji Yang — ORCID record. ORCID.
    https://orcid.org/0000-0002-8498-0119
  3. Computational Biologists Awards. (2026.)  Computational Biologists Awards.
    https://computationalbiologists.com/
  4. Research Article (2021. ) Clinicopathological features and resistance mechanisms in HIP1-ALK-rearranged lung cancer: A multicenter study.
    https://doi.org/10.1002/gcc.23005

Daojun Lv | Functional Genomics | Research Excellence Award

Published on by Computational Biologists

Research Excellence Award

Daojun Lv
Guangzhou Medical University

Daojun Lv
Affiliation Guangzhou Medical University
Country China
Scopus ID 56702091800
Documents 54
Citations 1,678
h-index 23
Subject Area Functional Genomics
Event Computational Biologists Awards
ORCID 0000-0002-3421-9647

Daojun Lv is affiliated with Guangzhou Medical University and is associated with research in functional genomics. The available Scopus information records 54 documents, 1,677 citations, and an h-index of 23, providing a bibliometric basis for describing the research profile. [1] The present article summarizes the supplied academic information and places the reported research indicators within the broader context of computational and genome-oriented biological research.

Abstract

Daojun Lv is a researcher affiliated with Guangzhou Medical University whose scholarly record includes work relevant to functional genomics. Bibliometric information lists 54 documents, 1,677 citations, and an h-index of 23 in Scopus. This profile presents these indicators alongside a discussion of research contributions, publication activity, research impact, and suitability for recognition through the Computational Biologists Awards. The article emphasizes scholarly information and avoids claims beyond the supplied bibliometric record. Functional genomics is considered as the subject area, providing context for understanding how computational and biological approaches can be integrated to investigate genes, molecular pathways, and genome-scale biological processes.

Keywords

Functional genomics, computational biology, genome-scale analysis, bioinformatics, genomic research, biological data analysis, molecular pathways, research impact, scholarly communication, Computational Biologists Awards.

Introduction

Functional genomics examines relationships between genomic information and biological function through experimental and computational approaches. Modern studies commonly integrate sequencing, transcriptomic, molecular, and computational datasets to characterize genes, pathways, and regulatory mechanisms. [2] Within this context, the supplied profile identifies Daojun Lv with Guangzhou Medical University and functional genomics as the principal subject area.

Research Profile

The research profile is characterized by an academic affiliation with Guangzhou Medical University and a subject classification in functional genomics. Scopus information supplied for this article reports 54 documents, 1,677 citations, and an h-index of 23. [1] These indicators provide quantitative context for describing the documented scholarly record.

Research Contributions

Functional genomics contributes to biological research by connecting genomic measurements with functional interpretation, often through computational analysis and integration of diverse molecular datasets. [2] Daojun Lv’s supplied subject classification places the profile within this research domain, although specific individual contributions should be assessed from verified publication records rather than inferred solely from bibliometric indicators.

Publications

The supplied Scopus record identifies 54 documents associated with the researcher profile. [1] Because individual publication titles, journals, publication years, and article-level citation data were not provided as source material for this page, no specific publication is attributed here. A complete publication assessment should rely on the authoritative Scopus record and verified article metadata.

Research Impact

The reported bibliometric indicators provide measurable evidence of scholarly visibility within the indexed record. The profile contains 1,677 citations and an h-index of 23 across 54 documents. [1] Citation counts and h-index values can describe patterns of scholarly attention, while their interpretation should consider field, publication age, database coverage, collaboration practices, and differences among research disciplines. [3]

Award Suitability

For a Research Excellence Award assessment, the supplied profile provides several documented elements for consideration, including affiliation, functional genomics subject classification, publication count, citation count, and h-index. [1] These indicators can form part of an evidence-based review, while a complete award evaluation would also require examination of research originality, methodological contribution, publication quality, broader influence, and independently verifiable scholarly achievements.

Conclusion

Daojun Lv’s supplied academic profile identifies Guangzhou Medical University as the institutional affiliation and functional genomics as the subject area. The reported Scopus indicators comprise 54 documents, 1,677 citations, and an h-index of 23. [1] These documented metrics provide a concise basis for presenting the researcher’s scholarly profile in connection with the Computational Biologists Awards.

References

  1. Elsevier. (n.d.). Scopus author details: Daojun Lv, Author ID 56702091800. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=56702091800
  2. Journal article. (2023). Exposure to elevated temperature affects the expression of PIWI-interacting RNAs and associated transcripts in mouse testes.
    https://doi.org/10.1111/andr.13381
  3. original article. (2026). LIPE-AS1 Facilitates Prostate Cancer Progression via Suppressing Cuproptosis Through the miR-330-3p/MGAT5 Axis.
    https://doi.org/10.1002/mog2.70098
  4. Computational Biologists Awards. (2026.). Official award website.
    https://computationalbiologists.com/
  5. ORCID. (n.d.). ORCID record: Daojun Lv, ORCID iD 0000-0002-3421-9647.
    https://orcid.org/0000-0002-3421-9647

Muhammad Arham | AI in Drug Discovery | Innovative Research Award

Published on by Computational Biologists

Innovative Research Award

Muhammad Arham
The University of Faisalabad, Pakistan

Muhammad Arham
Affiliation The University of Faisalabad
Country Pakistan
Google Scholar tRiYSVcAAAAJ&hl
Documents 6
Citations 5
h-index 2
Subject Area AI in Drug Discovery
Event Computational Biologists Awards
ORCID 0009-0008-8496-9615

Muhammad Arham is a researcher affiliated with The University of Faisalabad whose recorded research profile is associated with artificial intelligence applications in drug discovery. Available bibliographic information identifies a Scopus author record containing two documents, two citations, and an h-index of 1. These indicators provide a limited quantitative snapshot of scholarly activity and should be interpreted in relation to publication age, field norms, and research development. [1]

Abstract

Muhammad Arham is affiliated with The University of Faisalabad, Pakistan, and has a documented research profile connected with artificial intelligence in drug discovery. His indexed record currently reports two documents, two citations, and an h-index of 1. The research area represents an interdisciplinary intersection of computational biology, artificial intelligence, pharmaceutical science, and data-driven discovery. Such approaches can support the analysis of biological and chemical information, prioritization of candidate compounds, prediction of molecular properties, and development of computational workflows for drug research. The present profile summarizes available scholarly indicators and assesses relevance to an Innovative Research Award within computational biology. [1]

Keywords

Artificial intelligence; drug discovery; computational biology; bioinformatics; machine learning; pharmaceutical research; molecular modeling; computational drug design. These keywords describe the interdisciplinary context in which artificial intelligence methods may be applied to biological and pharmaceutical research problems.

Introduction

Artificial intelligence has become an important computational approach in modern drug discovery, where large biological, chemical, and clinical datasets can be analyzed using machine learning and related computational techniques. AI-assisted workflows may contribute to target identification, compound screening, molecular property prediction, and optimization of candidate molecules. [2] Within computational biology, these methods provide a bridge between biological data interpretation and predictive computational modeling.

Research Profile

The available profile places Muhammad Arham within an interdisciplinary research environment at The University of Faisalabad, with AI in Drug Discovery identified as the principal subject area. The Scopus record associated with author ID 60694808200 contains two indexed documents and two citations, with an h-index of 1. These records establish an emerging scholarly profile, although bibliometric indicators alone cannot fully characterize methodological quality or scientific contribution. [1]

Research Contributions

Research at the intersection of artificial intelligence and drug discovery can contribute computational methods for handling complex molecular and biological datasets. Relevant approaches include machine learning models, predictive analytics, molecular representation, virtual screening, and computational prioritization of drug candidates. [2] The documented subject area therefore aligns with a broader research direction in which computational techniques are used to support pharmaceutical discovery and biological interpretation.

Publications

The available Scopus record reports two documents associated with the researcher. Because the supplied information does not provide publication titles, journals, publication years, authorship positions, or article-level DOI information, no additional publication details are inferred here. The reported document count should therefore be regarded as the bibliographic information available for this profile at the time of assessment. [1]

Research Impact

The recorded profile currently has two citations and an h-index of 1. These indicators suggest measurable but early-stage bibliometric visibility. Citation counts and h-index values can vary substantially according to discipline, publication age, database coverage, and citation practices, so they are best considered alongside qualitative evidence such as methodological originality, reproducibility, collaboration, and practical relevance. [1]

Award Suitability

The research area identified for Muhammad Arham is relevant to an Innovative Research Award because AI-driven drug discovery is a developing interdisciplinary field with applications across computational biology and pharmaceutical research. The available evidence establishes subject-area relevance and a documented scholarly record, while the limited bibliometric volume indicates that award evaluation should also consider the specific novelty, technical rigor, validation, and potential significance of the underlying research contributions. [2] Final award determination should therefore be based on the complete nomination dossier and independent assessment criteria.

Conclusion

Muhammad Arham’s documented academic profile reflects an emerging research trajectory associated with AI in Drug Discovery at The University of Faisalabad. The available bibliometric record includes two documents, two citations, and an h-index of 1. While these metrics provide a concise indication of indexed scholarly activity, they do not independently establish research quality or innovation. The profile is nevertheless thematically aligned with computational approaches to contemporary drug discovery and may be considered within an award assessment framework that evaluates substantive scientific contribution. [1]

References

  1. Journal article. (2026). Harnessing Deep Learning Models for Guide RNA Optimization and Off-Target Prediction in CRISPR Systems.
    https://doi.org/10.1002/biot.70255
  2. Google Scholar. (n.d.). Rahim Zahedi, Author ID tRiYSVcAAAAJ&hl. Google Scholar author profile.
    https://scholar.google.com/citations?user=tRiYSVcAAAAJ&hl=en
  3. Journal article. (2026). Next-Generation Artificial Intelligence Strategies for Mechanistic Cancer Target Discovery and Drug Development: A State-of-the-Art Review.
    https://doi.org/10.1016/j.drudis.2018.11.014
  4. ORCID. (n.d.). ORCID record: Muhammad Arham. ORCID.
    https://orcid.org/0009-0008-8496-9615
  5. Computational Biologists Awards. (2026.). Official award website.
    https://computationalbiologists.com/