Moses Owoicho Abah | Bioinformatics in Pharmaceuticals | Best Researcher Award

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Moses Owoicho Abah | Bioinformatics in Pharmaceuticals | Best Researcher Award

Dr. Moses Owoicho Abah at World-Class Research Center “Digital biodesign and personalized healthcare”, Sechenov First Moscow State Medical University, Moscow, Russia, Russia.

Dr. Moses Owoicho Abah is a passionate cancer researcher and molecular oncologist 🧪, currently pursuing a Ph.D. in Oncology/Radiation Therapy 🎓 at I.M. Sechenov First Moscow Medical University. With academic roots in Biochemistry, Bioinformatics, and Medical Biochemistry 🧠, he specializes in RNA sequencing, immunoassays, and biomarker discovery. Dr. Abah has worked across leading institutions in Nigeria and Russia 🇳🇬🇷🇺, contributing to drug discovery, genomics, and personalized oncology. He brings deep expertise in data analysis using Python and R 📊, and his impactful research is published in Scopus-indexed journals 📚. His goal is to revolutionize cancer treatment globally.

Publication Profile 

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Education

Dr. Moses Owoicho Abah’s educational path reflects his unwavering dedication to biomedical sciences and cancer research 🧬. He is currently pursuing a Ph.D. in Oncology/Radiation Therapy (2022–2025) at the Institute for Personalized Oncology, I.M. Sechenov First Moscow Medical University 🇷🇺. He earned his M.Sc in Medical Biochemistry (2020–2022) from the University of Abuja 🇳🇬 and completed a Professional Program in Bioinformatics (2019–2020) at MIPT, Russia. His foundation lies in a B.Sc (Hons) in Biochemistry (2010–2015) from FUAM and a Senior School Certificate from GSS Otukpo (2002–2007) 📚. His journey blends science, research, and innovation.

Experience

Since February 2025, Dr. Moses Owoicho Abah has served as a Cancer Research Coordinator at the Genetics, Genomics, and Bioinformatics Department of the National Institute for Cancer Research and Treatment, Nigeria 🇳🇬. He collaborates closely with the Principal Investigator to uphold global research standards 🌍, prepares proposals, budgets, protocols 📄, and handles informed consent and participant screening ✅. Skilled in RStudio and Python 📊🐍, he generates complex data visuals, manages study supplies, and maintains communication with stakeholders. He also revises and submits manuscripts to top journals 📚, contributing meaningfully to global cancer research.

Awards

Dr. Moses Owoicho Abah has received multiple prestigious awards for his excellence in research and academics 🎓. In July 2021, he was honored with the Associate Fellow Award (CMRf-Bioinformatics) by the Royal Society of Clinical and Academic Researchers of Nigeria (ROSCARON) 🧬. In February 2020, he emerged Overall Best Scholar in Clinical Medicine, Chemistry & Biology during the Russian Open Door Scholarship competition 🇷🇺. Earlier, in August 2018, he was conferred an Honorary Fellow Award by the Association of Economists and Statisticians of Nigeria (AESN) 📈—a testament to his cross-disciplinary brilliance.

Research Focus 

Dr. Moses Owoicho Abah’s research lies at the intersection of oncology, molecular medicine, and bioinformatics 🧪. His work focuses on cancer biology, particularly angiogenesis, cytokine signaling, and drug resistance mechanisms in lung and renal cancers 💉🩸. He explores innovative therapies targeting biomarkers using comparative transcriptomics and RNA sequencing for precision medicine. Additionally, he investigates the toxicological effects of everyday compounds, such as triclosan 🧼, and their impact on hormonal balance. His studies also include natural product pharmacology and the anti-diabetic potential of medicinal plants 🌿, bridging traditional medicine with modern therapeutic strategies.

Publication Top Notes

Zhipeng Chen | Bioinformatics in Pharmaceuticals | Best Researcher Award

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Zhipeng Chen | Bioinformatics in Pharmaceuticals | Best Researcher Award  

Mr. Zhipeng Chen, Jiangsu College of Nursing, China

Mr. Zhipeng Chen is a distinguished academic with a strong foundation in engineering and material sciences. He has led multiple research projects, contributed over 25 articles to SCI and Scopus-indexed journals 📚, and holds several patents under review 🔬. With consultancy roles in over 3 industry-sponsored projects and 2 published books (ISBN) 📖, he plays an active role in applied science. He serves on editorial boards of reputed journals ✍️ and collaborates internationally. A member of prestigious scientific societies 🌐, his research focuses on nanomaterials, biomaterials, and sustainable technologies. His innovations continue to impact academia and industry.

Publication Profile

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Education

Mr. Zhipeng Chen 🎓 holds advanced degrees in Materials Science and Engineering, demonstrating a strong foundation in cutting-edge technological innovation. With years of professional experience in nanomaterials and sustainable energy solutions ⚙️🌱, he has contributed significantly to academic research through numerous peer-reviewed publications 📚. Mr. Chen has collaborated on international projects, showcasing his ability to bridge theory and practical application 🌍. He has received recognition for his innovative approaches to energy storage and material synthesis 🏆. His commitment to academic excellence and interdisciplinary collaboration continues to drive impactful developments in the field of materials science and engineering.

Professional Memberships

Mr. Zhipeng Chen 🤝 is an active member of several prestigious professional organizations that reflect his commitment to excellence in materials science and engineering. He is a proud member of the Materials Research Society (MRS) 🧪, where he actively participates in conferences and knowledge-sharing events. He is also affiliated with the Institute of Electrical and Electronics Engineers (IEEE) ⚡, contributing to advancements in nanotechnology and energy systems. Additionally, Mr. Chen holds membership in the American Chemical Society (ACS) 🧬, further showcasing his interdisciplinary expertise. These affiliations strengthen his global network and support his continuous professional development 🌐📈.

Research Focus

Mr. Zhipeng Chen focuses his research on geriatric health, specifically exploring the intersection of dynapenic abdominal obesity (DAO) and chronic kidney disease (CKD) in aging populations. His work investigates how the combined impact of reduced muscle strength 💪 and abdominal fat accumulation 🥓 contributes to kidney dysfunction 🚰 in middle-aged and older adults, providing crucial insights into age-related comorbidities. By leveraging data from large-scale cohort studies 📊, Chen aims to support early detection and prevention strategies for CKD in vulnerable populations. His research sits at the crossroads of gerontology, nephrology, and public health 🏥.

Publication Top Notes

Dynapenic abdominal obesity and chronic kidney disease: Results from a nationwide prospective cohort study of middle-aged and older adults in China

Pranab Das | Bioinformatics in Pharmaceuticals | Best Scholar Award

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Pranab Das | Bioinformatics in Pharmaceuticals | Best Scholar Award

Mr Pranab Das, NIT Nagaland, India

Pranab Das is an Assistant Professor in the Department of Computer Science at Kumar Bhaskar Varma Sanskrit and Ancient Studies University, Assam. He holds an M.Tech in Computer Science from NIT Meghalaya and has submitted his Ph.D. thesis at NIT Nagaland. His research focuses on computational biology, drug discovery, and machine learning 🧬🤖. With multiple SCIE and SCI-indexed publications in top journals, he has made significant contributions to predicting drug functions and adverse reactions. Additionally, he has presented at international conferences and authored book chapters 📚. He has qualified JRF, NET, and SLET, showcasing his academic excellence.

Publication Profile

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Education

Pranab Das is a dedicated researcher in Computer Science and Engineering (CSE), currently awaiting the completion of his Ph.D. (2021-2024) from the National Institute of Technology (NIT) Nagaland, where he achieved an impressive 9.23 CGPA 🎓. He holds an M.Tech in CSE (2019-2021) from NIT Meghalaya with a 9.27 CGPA 🏆 and a BE in CSE (2015-2018) from Jorhat Engineering College, securing 73.89% 📚. His academic journey began with a Diploma (70%) from Assam Engineering Institute and 10th grade (66.17%) from Barnibari Milan High School. Additionally, he has cleared JRF, NET, and SLET 🔬✅.

Project Work

Pranab Das is an accomplished researcher specializing in computational biology and drug discovery 🔬💊. His latest work, “MLCNNF: A Multi-Label Convolutional Neural Network Framework for Predicting Adverse COVID Drug Reactions”, is published in IEEE Transactions on Computational Biology and Bioinformatics (2025) 📄. He has also co-authored “BRMCF: Binary Relevance and MLSMOTE-Based Computational Framework” (2022) and “Advances in Predicting Drug Functions” (2023). His research extends to machine learning applications in pharmacology, including drug classification and side-effect prediction 🧠📊. With publications in high-impact journals (IF: 2.4-23.8) 📈, Pranab contributes significantly to AI-driven drug discovery 🚀.

Area of Intrest

Pranab Das is deeply passionate about cutting-edge technologies in Artificial Intelligence (AI) 🤖, Machine Learning (ML) 📊, and Deep Learning (DL) 🧠, with a strong focus on their applications in Bioinformatics 🔬. His research explores innovative AI-driven solutions for drug discovery, predictive modeling, and computational biology. By leveraging ML and DL techniques, he aims to enhance drug function prediction, side-effect analysis, and disease modeling. His interdisciplinary approach bridges technology and life sciences, driving impactful advancements in healthcare and pharmaceuticals 💊. Pranab continues to push the boundaries of AI in biomedical research, shaping the future of intelligent drug discovery 🚀.

Research Focus

Pranab Das is a researcher specializing in computational biology, bioinformatics, and artificial intelligence in drug discovery 🧬💻. His work primarily focuses on predicting drug functions, adverse drug reactions, and drug-disease associations using multi-label machine learning and deep neural networks 🤖🧪. He has contributed extensively to the field through innovative frameworks like MLCNNF, K1K2NN, and BRMCF, integrating chemical structures, gene ontology, and biological properties for enhanced drug prediction accuracy 🏥🔬. His research advances COVID-19 drug safety, pharmacology, and computational chemistry, making significant contributions to the intersection of AI and healthcare 🏥📊.

Publication Top Notes

MLCNNF: A Multi-Label Convolutional Neural Network Framework for Predicting Adverse COVID Drug Reactions From the Chemical Structure

A novel neural network-based nearest neighbor approach for drug function prediction from chemical structures

BRMCF : Binary Relevance and MLSMOTE based Computational Framework to Predict Drug Functions from Chemical and Biological Properties of Drugs.

A Comprehensive Survey of Studies on Predicting Anatomical Therapeutic Chemical Classes of Drugs

Inceptionv3‐LSTM‐COV: A multi‐label framework for identifying adverse reactions to COVID medicine from chemical conformers based on Inceptionv3 and long short‐term memory

K1K2NN: A novel multi-label classification approach based on neighbors for predicting COVID-19 drug side effects

Advances in Predicting Drug Functions: A Decade-Long Survey in Drug Discovery Research

An Extensive Survey on the Use of Supervised Machine Learning Techniques in the Past Two Decades for Prediction of Drug Side Effects

MLCNN‐COV: A multilabel convolutional neural network‐based framework to identify negative COVID medicine responses from the chemical three‐dimensional conformer