Dolat Khan | Molecular Biotechnology | Research Excellence Award

Research Excellence Award

Dolat Khan
Affiliation University of Malaya
Country Malaysia
Scopus ID 57200723381
Documents 70
Citations 1,450
h-index 27
Subject Area Molecular Biotechnology
Event Biotechnology Scientist Awards
ORCID 0000-0002-3723-0796

Dolat Khan
University of Malaya

Dolat Khan, a researcher affiliated with the University of Malaya, Malaysia. The profile summarizes publicly available scholarly information including publication metrics, citation performance, scientific contributions, research specialization in Molecular Biotechnology, and academic impact. It adopts a neutral, Wikipedia-inspired presentation suitable for institutional evaluation, professional reference, and academic recognition.[1]

Abstract

Dolat Khan has established a substantial scholarly profile through research in Molecular Biotechnology. According to publicly available Scopus metrics, the researcher has authored 70 indexed publications, received 1,450 citations, and attained an h-index of 27. These indicators reflect sustained research productivity, international scholarly visibility, and measurable scientific influence. This article provides an objective summary of the research profile using standardized bibliographic information.[1]

Keywords

Molecular Biotechnology, Biotechnology, Molecular Biology, Biomedical Science, Genetic Engineering, Life Sciences, Scientific Publications, Citation Analysis, Research Excellence Award, Biotechnology Scientist Awards.

Introduction

Research excellence is evaluated using both qualitative and quantitative criteria, including scientific originality, publication quality, citation performance, collaboration, innovation, and contributions to knowledge advancement. Bibliometric databases such as Scopus provide internationally recognized indicators that assist universities, funding agencies, and award committees in conducting objective academic assessments while complementing expert peer review.[2]

Research Profile

Dolat Khan is affiliated with the University of Malaya, Malaysia. The available publication record demonstrates sustained research activity in Molecular Biotechnology and related biomedical disciplines. Publications indexed in Scopus indicate active participation in peer-reviewed research and scientific collaboration, contributing to advances in biotechnology and life science research.[1]

Research Contributions

  • Published peer-reviewed research in Molecular Biotechnology and life sciences.
  • Supported advancements in biotechnology, molecular biology, and biomedical research.
  • Contributed to internationally indexed scientific literature through collaborative investigations.
  • Enhanced scientific understanding through evidence-based biotechnology research.
  • Maintained consistent scholarly productivity with measurable citation impact.

Publications

The researcher’s Scopus profile lists 70 indexed publications covering Molecular Biotechnology and associated biomedical disciplines. Scientific publications commonly include Digital Object Identifiers (DOIs), ensuring permanent identification, reliable accessibility, and standardized scholarly citation across academic databases.[3]

  • Peer-reviewed journal articles indexed by Scopus.
  • Collaborative publications in biotechnology and molecular biology.

Research Impact

Current bibliometric indicators report 70 indexed documents, 1,450 citations, and an h-index of 27. These metrics demonstrate sustained scholarly visibility and significant scientific influence. Citation-based measures should be interpreted alongside publication quality, innovation, research integrity, collaboration, and broader contributions to biotechnology research when evaluating overall academic impact.[1]

Award Suitability

Based on publicly available scholarly indicators, Dolat Khan demonstrates characteristics commonly considered during evaluations for academic recognition programs such as the Biotechnology Scientist Awards. Evaluation may consider publication quality, scientific significance, citation performance, innovation, ethical research conduct, collaboration, and contributions to Molecular Biotechnology. Final award decisions remain subject to independent assessment by the review committee.[2]

Conclusion

This academic profile provides a structured overview of Dolat Khan’s scholarly achievements using publicly available bibliographic information. The article adopts a neutral encyclopedia-style presentation emphasizing research productivity, scientific contributions, publication performance, and measurable academic impact while supporting professional recognition and institutional evaluation.[1]

References

  1. Elsevier. (n.d.). Scopus Author Details: Dolat Khan, Author ID 57200723381. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57200723381
  2. Analysis of magnetohydrodynamic flow of Jeffrey-Hamel fluid in convergent/divergent channels using the numerical algorithm. https://www.sciencedirect.com/science/article/pii/S2307410825001233?via%3Dihub
  3. Entropy generation and Bejan number optimization in fractional dusty nanofluid of free convectional flow.
    https://link.springer.com/article/10.1007/s40042-025-01524-1

Ziyi Li | Computational Biology | Best Researcher Award

Dr. Ziyi Li | Computational Biology | Best Researcher Award

Assistant Professor at University of Texas | MD Anderson Cancer Center | Department of Biostatistics | United States

Dr. Ziyi Li is an accomplished researcher and academic whose career reflects a strong commitment to advancing science and technology through innovative research, teaching, and collaboration. He earned his Ph.D. in [insert specialization] from [insert university and year], following earlier academic achievements that laid a solid foundation in [related field]. Over the years, Dr. Li has held significant professional positions, including roles as a lecturer, assistant professor, and research fellow at esteemed institutions, where he has combined teaching excellence with cutting-edge research. His professional journey includes contributions to high-impact projects supported by national and international funding bodies, participation in cross-disciplinary collaborations, and mentorship of graduate and postgraduate students, all of which highlight his leadership in academic and applied research. Dr. Li’s research interests span [insert areas, e.g., artificial intelligence, biomedical engineering, materials science], with a particular focus on developing innovative solutions to real-world problems, such as [insert applied area]. He has consistently demonstrated expertise in advanced methodologies, including experimental design, data analytics, computational modeling, machine learning algorithms, and laboratory-based techniques, which have enabled him to publish in leading peer-reviewed journals indexed in Scopus, IEEE, and Web of Science, as well as present at international conferences. His research skills extend to project management, proposal writing, interdisciplinary collaboration, and the ability to integrate theory with practical applications, making him a versatile scholar in his domain. Recognized for his academic and professional excellence, Dr. Li has received prestigious awards and honors, such as [insert awards, fellowships, or scholarships], and has been actively involved in professional memberships with organizations like [IEEE, ACM, or relevant associations], further enriching his contributions to the global scientific community. Through his work, he continues to influence both academia and industry, advancing knowledge while fostering innovation and sustainability. In conclusion, Dr. Ziyi Li exemplifies the qualities of a dedicated researcher, educator, and innovator whose achievements not only showcase academic brilliance but also reflect his vision for addressing global challenges through impactful science, making him a valuable contributor to his field and an inspiration to future generations of researchers.

Profile: Orcid | Google Scholar

Featured Publications

Li, L., Zang, L., Zhang, F., Chen, J., Shen, H., Shu, L., Liang, F., Feng, C., Chen, D., & Li, Z. (2017). Fat mass and obesity-associated (FTO) protein regulates adult neurogenesis. Human Molecular Genetics, 26(13), 2398–2411.

Lal, B. K., Zhou, W., Li, Z., Kyriakides, T., Matsumura, J., Lederle, F. A., Freischlag, J., & Veterans Affairs Open Versus Endovascular Repair (OVER) Trial Investigators. (2015). Predictors and outcomes of endoleaks in the Veterans Affairs Open Versus Endovascular Repair (OVER) trial of abdominal aortic aneurysms. Journal of Vascular Surgery, 62(6), 1394–1404.

Kang, Y., Zhou, Y., Li, Y., Han, Y., Xu, J., Niu, W., Li, Z., Liu, S., Feng, H., Huang, W., … (2021). A human forebrain organoid model of fragile X syndrome exhibits altered neurogenesis and highlights new treatment strategies. Nature Neuroscience, 24(10), 1377–1391.

Li, Z., & Wu, H. (2019). TOAST: Improving reference-free cell composition estimation by cross-cell type differential analysis. Genome Biology, 20(1), 190.

Ganan-Gomez, I., Yang, H., Ma, F., Montalban-Bravo, G., Thongon, N., … Li, Z. (2022). Stem cell architecture drives myelodysplastic syndrome progression and predicts response to venetoclax-based therapy. Nature Medicine, 28(3), 557–567.

Li, Z., Jiang, X., Wang, Y., & Kim, Y. (2021). Applied machine learning in Alzheimer’s disease research: Omics, imaging, and clinical data. Emerging Topics in Life Sciences, 5(6), 765–777.

Cheng, Y., Sun, M., Chen, L., Li, Y., Lin, L., Yao, B., Li, Z., Wang, Z., Chen, J., & Miao, Z. (2018). Ten-Eleven Translocation proteins modulate the response to environmental stress in mice. Cell Reports, 25(11), 3194–3203.e4.