Subrata Sinha| Bioinformatics| Editorial Board Member

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Assist Prof Dr. Subrata Sinha| Bioinformatics| Editorial Board Member

Assistant Professor | Dibrugarh University | India

Dr. Subrata Sinha is a distinguished researcher and academic affiliated with Brainware University, Kolkata, India, specializing in computational biology, bioinformatics, and machine learning applications in biomedical research. His expertise spans the development and application of advanced computational models, including convolutional neural networks for brain tumor classification, in silico pharmacophore modeling, and network pharmacology analyses for therapeutic discovery. Dr. Sinha has contributed significantly to bridging computational techniques with practical biomedical applications, demonstrating a strong commitment to translational research that benefits both scientific advancement and societal health outcomes. Over his career, he has published extensively in peer-reviewed journals, fostering collaborations with a wide network of international co-authors and research groups. His work emphasizes precision medicine, predictive modeling, and integrative approaches that combine molecular insights with computational strategies to address complex biomedical challenges. Dr. Sinha’s research not only advances academic understanding but also holds potential for real-world applications in diagnostics, drug discovery, and healthcare technology development. His contributions are recognized for their methodological rigor, innovative approach, and relevance to pressing global health issues. Dr. Sinha’s academic influence and research productivity are reflected in his metrics: 78 citations, 36 documents, and an h-index of 4.

Profiles: Scopus | ORCID

Featured Publications

Akermi, S., Chaari, M., Elhadef, K., Sharma, A., Dey, A., Choudhary, A., Sinha, S., Festuccia, R., Mellouli, L., & Smaoui, S. (2025). Bioactive compounds and cancer prevention: A nutritional approach. In Unleashing the Power of Functional Foods and Novel Bioactives (pp. xx–xx). Elsevier.

Sinha, S., Mali, S., Pathak, A. K., & Rajkhowa, S. (2025). BRAIN-SCN-PRO: A machine learning model for the classification of brain tumors using a convolutional neural network architecture. Biomedical Signal Processing and Control.

Akermi, S., Sharma, A., Dey, A., Chaari, M., Elhadef, K., Choudhary, A., Sinha, S., Mellouli, L., & Smaoui, S. (2025). Functional foods and aging and antiaging: A recipe for longevity. In Unleashing the Power of Functional Foods and Novel Bioactives (pp. xx–xx). Elsevier.

Sinha, S., Mali, S., & Rajkhowa, S. (2025). High-precision lung cancer classification with custom CNN: Evaluation and transfer learning for broader cancer types. Procedia Computer Science.

Mali, S., & Sinha, S. (2025). Histopathological image processing for lung carcinoma classification: A comparative study of stain normalization methods for CNN-based analysis. In 6th IEEE International Conference on Recent Advances in Information Technology (RAIT 2025) (pp. xx–xx). IEEE.

Shishir K Gupta | Bioinformatics | Best Researcher Award

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Dr. Shishir K Gupta | Bioinformatics | Best Researcher Award

Assistant Professor | Centre of BioMedical Research | India

Dr. Shishir Kumar Gupta is an Assistant Professor in the Department of Data Sciences at the Centre of BioMedical Research (CBMR), SGPGIMS Campus, Lucknow, India. He earned his Ph.D. in Bioinformatics from the Julius-Maximilians-Universität Würzburg, Germany (2016), focusing on genome re-annotation and immune transcriptome analysis in insects. His research expertise spans Network Science, Bioinformatics, Multi-omics Data Integration, Big Data Analytics, and Machine Learning, with applications in computational modeling of biological systems, understanding disease mechanisms, and developing therapeutic strategies. Dr. Gupta has extensive postdoctoral experience from renowned German institutions, including the University of Würzburg, Heinrich Heine University Düsseldorf (CEPLAS), and University Hospital Erlangen, where he led interdisciplinary projects in systems biology, genomics, and computational immunology. He has authored over 45 peer-reviewed publications and book chapters in high-impact journals such as Frontiers in Immunology, International Journal of Molecular Sciences, and Computational and Structural Biotechnology Journal, and serves as a reviewer for leading journals including Nature Scientific Reports, BMC Bioinformatics, and PLOS Computational Biology. His supervision of graduate students and teaching roles in bioinformatics, genomics, and systems biology at both Indian and European institutions reflect his commitment to academic excellence. Through international collaborations and data-driven research, Dr. Gupta aims to advance precision medicine, network-based drug discovery, and the integration of computational and experimental approaches to address global challenges in infectious diseases, cancer biology, and immunology, thereby contributing to improved healthcare and scientific innovation.

Profiles:  Google Scholar | Scopus | ORCID 

Featured Publications

Kupper, M., Gupta, S. K., Feldhaar, H., & Gross, R. (2014). Versatile roles of the chaperonin GroEL in microorganism–insect interactions. FEMS Microbiology Letters, 353(1), 1–10.

Kaltdorf, M., Srivastava, M., Gupta, S. K., Liang, C., Binder, J., Dietl, A. M., Meir, Z., Haas, H., Osherov, N., & Krappmann, S. (2016). Systematic identification of anti-fungal drug targets by a metabolic network approach. Frontiers in Molecular Biosciences, 3, 22.

Gupta, S. K., Kupper, M., Ratzka, C., Feldhaar, H., Vilcinskas, A., Gross, R., & Förster, F. (2015). Scrutinizing the immune defence inventory of Camponotus floridanus applying total transcriptome sequencing. BMC Genomics, 16(1), 1–21.

Srivastava, M., Gupta, S. K., Abhilash, P. C., & Singh, N. (2012). Structure prediction and binding sites analysis of curcin protein of Jatropha curcas using computational approaches. Journal of Molecular Modeling, 1–9.

Akhoon, B. A., Singh, K. P., Varshney, M., Gupta, S. K., Shukla, Y., & Gupta, S. K. (2014). Understanding the mechanism of atovaquone drug resistance in Plasmodium falciparum cytochrome b mutation Y268S using computational methods. PLoS ONE, 9(10), e110041.

Dr. Shishir Kumar Gupta’s research integrates computational modeling, network science, and multi-omics data analysis to uncover molecular mechanisms of diseases and identify novel therapeutic strategies. His work advances precision medicine and drug discovery, bridging bioinformatics innovation with real-world biomedical and societal impact through data-driven solutions for global health challenges.

Jiaxing Chen | Bioinformatics | Best Researcher Award

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🌟Dr. Jiaxing Chen, Bioinformatics, Best Researcher Award🏆

  • Doctorate at BNU-HKBU United International College, Hong Kong

Jiaxing CHEN, Ph.D., is an accomplished researcher and educator with expertise in bioinformatics, machine learning, and algorithms. With a background in computer science, Jiaxing has made significant contributions to understanding complex biological systems through computational analysis. Jiaxing’s research focuses on omics-abundance, single-cell analysis, and spatial transcriptomics, aiming to unravel intricate biological processes at the molecular level. With a passion for teaching, Jiaxing has also imparted knowledge and mentored students in various computer science and bioinformatics courses.

Author Metrics:

Scopus Profile

Google Scholar Profile

Jiaxing CHEN has established a strong presence in the academic community with a notable publication record and contributions to several high-impact journals. Their publications have garnered attention for their innovative approaches in bioinformatics and computational biology. Additionally, Jiaxing’s work has been cited by peers, indicating its relevance and impact within the scientific community.

Citations: Jiaxing CHEN has received a total of 291 citations across 287 documents, indicating the impact and recognition of their research within the academic community.

Documents: Jiaxing CHEN has authored 12 documents indexed in the database.

Education:

Jiaxing CHEN earned a Ph.D. in Computer Science from City University of Hong Kong, under the supervision of Prof. Shuaicheng Li. Prior to that, they completed a Bachelor of Engineering in Computer Science at Nankai University. Jiaxing also enriched their academic experience as a visiting scholar at UC Berkeley, collaborating with Prof. Steve Smale in the Department of Mathematics.

Research Focus:

Jiaxing CHEN’s research interests revolve around bioinformatics, machine learning, and algorithms. They are particularly interested in leveraging computational techniques to analyze omics-abundance data, single-cell gene expression, and spatial transcriptomics. By applying advanced computational methods, Jiaxing aims to elucidate complex biological phenomena and uncover novel insights into gene regulation and cellular behavior.

Professional Journey:

Jiaxing CHEN has embarked on a dynamic professional journey, starting as a Bioinformatics Analyst intern at BGI before pursuing a Ph.D. in Computer Science. Following their doctoral studies, Jiaxing served as a Postdoc in Computer Science at Hong Kong Baptist University before assuming the role of Assistant Professor at Beijing Normal University-Hong Kong Baptist University United International College. Throughout their career, Jiaxing has continuously contributed to cutting-edge research in bioinformatics and computational biology.

Honors & Awards:

Jiaxing CHEN has received recognition for their contributions to the field of bioinformatics and computational biology. They have been honored with prestigious awards such as the Young Scientists Fund of the National Natural Science Foundation of China (NSFC) for their outstanding research endeavors. Additionally, Jiaxing’s publications have been well-received, earning them accolades within the scientific community.

Publications Noted & Contributions:

Jiaxing CHEN has authored numerous impactful publications that have significantly advanced the field of bioinformatics. Their research spans a wide range of topics, including the reconstruction of gene regulatory networks, inference of direct regulatory interactions, and the analysis of gene expression profiles. Jiaxing’s contributions have shed light on key biological processes, such as horizontal gene transfer in gut microbiota and genetic differentiation in skeletal muscle.

On Triangle Inequalities of Correlation-based Distances for Gene Expression Profiles

  • Authors: J Chen, YK Ng, L Lin, X Zhang, S Li
  • Journal: BMC Bioinformatics
  • Volume: 24
  • Issue: 1
  • Pages: 40
  • Citation Count: 12
  • Year: 2023

Association between Metabolic Status and Gut Microbiome in Obese Populations

  • Authors: Q Zeng, Z Yang, F Wang, D Li, Y Liu, D Wang, X Zhao, Y Li, Y Wang, …
  • Journal: Microbial Genomics
  • Volume: 7
  • Issue: 8
  • Pages: 000639
  • Citation Count: 11
  • Year: 2021

dynDeepDRIM: A Dynamic Deep Learning Model to Infer Direct Regulatory Interactions Using Time-Course Single-Cell Gene Expression Data

  • Authors: Y Xu, J Chen, A Lyu, WK Cheung, L Zhang
  • Journal: Briefings in Bioinformatics
  • Volume: 23
  • Issue: 6
  • Pages: bbac424
  • Citation Count: 5
  • Year: 2022

Both Simulation and Sequencing Data Reveal Coinfections with Multiple SARS-CoV-2 Variants in the COVID-19 Pandemic

  • Authors: Y Li, Y Jiang, Z Li, Y Yu, J Chen, W Jia, YK Ng, F Ye, SC Li, B Shen
  • Journal: Computational and Structural Biotechnology Journal
  • Volume: 20
  • Pages: 1389-1401
  • Citation Count: 5
  • Year: 2022

KDiamend: A Package for Detecting Key Drivers in a Molecular Ecological Network of Disease

  • Authors: M Lyu, J Chen, Y Jiang, W Dong, Z Fang, S Li
  • Journal: BMC Systems Biology
  • Volume: 12
  • Pages: 89-99
  • Citation Count: 5
  • Year: 2018

Research Timeline:

Jiaxing CHEN’s research trajectory showcases a continuous commitment to exploring innovative approaches in bioinformatics and computational biology. From their early experiences as a Bioinformatics Analyst intern to their current role as an Assistant Professor, Jiaxing has consistently pursued cutting-edge research projects aimed at unraveling the complexities of biological systems. Their research timeline reflects a passion for discovery and a dedication to advancing knowledge in the field.

Collaborations and Projects:

Jiaxing CHEN has collaborated with esteemed researchers and institutions on various interdisciplinary projects in bioinformatics and computational biology. Their collaborative efforts have resulted in impactful contributions to understanding gene regulatory networks, genetic variation, and microbial ecology. Through collaborative projects, Jiaxing has fostered connections within the scientific community and expanded the scope of their research endeavors.