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/

Zhang Xiaoming | Pharmacogenomics Modeling | Best Researcher Award

Published on by Computational Biologists

Dr. Zhang Xiaoming | Pharmacogenomics Modeling | Best Researcher Award 

Associate research fellow at National Institutes for Food and Drug Control, China.

Dr. Xiaoming Zhang is an Associate Professor at the National Institutes for Food and Drug Control, Beijing, with a strong background in molecular biology and biopharmaceutical research. He holds a Ph.D. in Life Sciences from Peking University and has held research positions at both Peking University and the National University of Singapore. His work focuses on the development of innovative reporter gene assays for evaluating therapeutic protein and peptide bioactivity. With multiple first-author publications in high-impact journals and international research experience, Dr. Zhang is recognized for his contributions to translational research and regulatory science.

🎓 Academic Background:

Dr. Xiaoming Zhang began his scientific journey with a Bachelor’s degree in Life Sciences from Hebei University (2003–2007), laying a strong foundation in biological research. Driven by a deep curiosity for life at the molecular level, he pursued his Ph.D. in Life Sciences at the prestigious Peking University (2007–2012), where he delved into advanced molecular biology and genetics. His academic rigor and commitment to scientific excellence during this formative phase established the groundwork for a successful research career.

Profile:

🧪 Professional Experience:

Dr. Zhang’s professional trajectory is marked by steady progress and international exposure. He first worked as a Research Assistant at the School of Chemical Biology & Biotechnology, Peking University (2012–2013), contributing to innovative biochemical studies. In 2013, he joined the Department of Biochemistry at Yong Loo Lin School of Medicine, National University of Singapore, where he served as a Research Fellow for nearly six years. Here, he refined his expertise in translational research and therapeutic bioassays. Since March 2019, Dr. Zhang has been serving as an Associate Professor at the National Institutes for Food and Drug Control in Beijing, playing a key role in therapeutic evaluations and regulatory science.

📚 Research Contributions:

Dr. Zhang is renowned for his pioneering work in the development of reporter gene assays to evaluate the biological activities of therapeutic proteins and peptides. His research spans a broad spectrum—from PEGylated recombinant human growth hormone to glucagon-like peptide-2 analogues, addressing critical needs in drug development. Notably, his recent publications in Journal of Pharmaceutical Analysis, Molecules, and iScience highlight his innovative approaches to bioassay design and therapeutic evaluation. His co-authorship and first-author roles in multiple peer-reviewed journals underscore his direct involvement in impactful discoveries.

🏅 Recognition and Impact:

While Dr. Zhang’s scientific publications speak volumes, his true impact lies in the translation of molecular insights into therapeutic assessment tools. His work contributes significantly to drug safety and efficacy testing, ensuring that biologics are accurately evaluated before reaching patients. As an Associate Professor at a national regulatory institute, his role bridges academic innovation and public health policy, making his contributions both scientifically rigorous and socially relevant.

🚀 Future Potential:

Dr. Xiaoming Zhang’s career demonstrates an upward trajectory with great potential for further leadership in biopharmaceutical regulation and translational research. With continued contributions to therapeutic bioactivity assays, regulatory innovation, and interdisciplinary collaborations, Dr. Zhang stands out as a valuable contributor to global health sciences. He is a strong contender for prestigious recognitions such as the Best Researcher Award, and his journey is a testament to dedication, innovation, and scientific excellence.

Publications:

  1. An improved reporter gene assay for evaluating the biological activity of recombinant human growth hormone
    Journal of Pharmaceutical Analysis, 2025

    • Authors: Xiaoming Zhang, Heyang Li, Ying Huang, Ping Lv, Lvyin Wang, Kezheng Xu, Yi Li, Xinyue Hu, Yue Sun, Cheng-gang Liang, Jing Li

  2. Development of a Mechanism of Action-Reflective Cell-Based Reporter Gene Assay for Measuring Bioactivities of Therapeutic Glucagon-like Peptide-2 Analogues
    Molecules, 2025

  3. A Reporter Gene Assay for Measuring the Biological Activity of PEGylated Recombinant Human Growth Hormone
    Molecules, 2025

    • Authors: Shaowang Hu*, Xiaoming Zhang*, Yi Li, Jing Li, Yingwu Wang, Chenggang Liang

    • (Co-first author)

  4. MLL5 regulates Rhodopsin gene expression by acting as a novel coactivator of CRX
    iScience, 2022

    • Authors: Zhang XM, Zhang BW, Xiang L, Wu H, Zhou PP, Alexander SAS, Zhou P, Dai MZ, Wang X, Xiong W, Zhang Y, Jin ZB, Deng LW

  5. MLL5 (KMT2E): structure, function, and clinical relevance
    Cellular and Molecular Life Sciences, 2017

    • Authors: Zhang XM, Novera W, Zhang Y, Deng LW

  6. Pluripotent Stem Cell Protein Sox2 Confers Sensitivity towards LSD1 Inhibition in Cancer Cells
    Cell Reports, 2013

    • Authors: Xiaoming Zhang, Fei Lu, Jing Wang, Feng Yin, Zhengshuang Xu, Dandan Qi, Yuwen Cao, Weihua Liang, Yuqing Liu, Yundong Wu, Hong Sun, Tao Ye, Hui Zhang