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/

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/

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