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Computational Biology for Stem Cell Research

1st Edition - February 1, 2024

Editors: Pawan Raghav, Rajesh Kumar, Anjali Lathwal, Navneet Sharma

Paperback ISBN:

9 7 8 - 0 - 4 4 3 - 1 3 2 2 2 - 3

Computational Biology for Stem Cell Research seamlessly bridges the gap between the worlds of biomedical sciences and in silico computational methods. This book serves as a… Read more

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Computational Biology for Stem Cell Research seamlessly bridges the gap between the worlds of biomedical sciences and in silico computational methods. This book serves as a valuable resource for researchers and students, enabling them to grasp and delve into the intricacies of hematopoietic Stem Cells (HSCs) and mesenchymal Stem Cells (MSCs) through the lens of computational biology. This perspective sheds light on stem cell transplantation, translational research, and unique properties of stem cells like self-renewal and differentiation. In addition to introducing readers to stem cell-focused bioinformatics tools, this resource offers a clear pathway for effortlessly merging in silico methods with traditional in vitro and in vivo approaches.

Computational Biology for Stem Cell Research combines science and technology to showcase how computational methods transform stem cell research by reducing costs and enhancing investigations. The chapters uncover various approaches, from machine learning to genome analysis, for studying networks, protein interactions, dynamics, and the preprocessing of large datasets. The book aims to give readers a broad view of the advanced computational tools and methods extensively employed in stem cell research. Additionally, the book emphasizes the ongoing studies and tools yet to be developed for furthering stem cell research.

Section I – In silico Tools and Approaches in Stem Cell Biology 1. Advancement of In Silico Tools in Stem Cell Research 2. Comparative Study of Bioinformatics Approaches in Stem Cell Biology 3. Stem Cell Informatics: Web-Resources Aiding in Stem Cell Research 4. Stem Cell-Based Informatics Development and Approaches 5. Application of Machine Learning-Based Approaches in Stem Cell Research 6. Stem Cell and Stem Cell Therapy in the Era of Machine Learning: A Mini Review 7. Computational and Stem Cell Biology: Challenges and Future Perspectives Section II – Application of Genomic, Proteomic Approaches in Stem Cell Research 8. Single Cell Transcriptome Profiling in Unravelling Distinct Molecular Signatures from Cancer Stem Cells 9. The Single-Cell Big Data Analytics: A Game-Changer in Bioscience 10. A Systematic Genomics and Proteomics Aspects for Understanding the Stemness Phenotype in Stem Cells 11. Cutting-Edge Proteo-Genomics Approaches to Analyze Stem Cells at the Therapeutic Level 12. Advances in Regenerative Medicines Based on Mesenchymal Stem Cell Secretome 13. Paradigms of Omics in Bioinformatics for Accelerating Current Trends and Future Prospects of Stem Cell Research 14. Transcriptomic Profiling-Based Identification of Predictive and Prognostic Biomarkers of Stem Cells 15. Genomic and Transcriptomic Applications in Neural Stem Cell Therapeutics Section III – Stem Cell Network Modeling and Systems Biology 16. Integration of Multi-Lmic Data to Identify Transcriptional Targets During Human Hematopoietic Stem Cell Differentiation 17. Computational Approaches to Determine Stem Cell Fate 18. Stem Cell Databases and Tools: Challenges and Opportunities for Computational Biologists 19. Deciphering the Complexities of Stem Cells Through Network Biology Approaches for their Application in Regenerative Medicine 20. Bioinformatics Approaches to the Understanding of Notch Signaling in the Biology of Stem Cells 21. In Silico Approaches for the Analyses of Developmental Fate of Stem Cells 22. Understanding Stem Cell Biology: Differentiation and Characterization - an Overview 23. Computational Approaches for Hematopoietic Stem Cells 24. Approaches to Construct and Analyze Stem Cells Regulatory Networks Section IV – Computational Approaches for Stem Cell Tissue Engineering 25. Computational Tissue Engineering in Chondral Defect 26. Recent Advances in Computational Modeling: An Appraisal of Stem Cell and Tissue Engineering Research 27. Computational Approaches for Bioengineering of Cornea 28. Cheminformatics, Metabolomics and Stem Cell Tissue Engineering: A Transformative Insight 29. Targeting Cancer Stem Cells Combined with the Power of Computational Tools Offer New Strategy for Radiotherapy 30. Introduction to Machine Learning and its Applications in Stem Cell Research 31. Multiscale Computational and Machine Learning Models for Designing Stem Cell-Based Regenerative Medicine Therapies 32. Computational Analysis of Epithelial Tissue Regeneration

Pawan Raghav

Dr. Pawan Kumar Raghav completed his MSc in Bioinformatics (2008) from Punjabi University Patiala, India; PG Diploma in Chemoinformatics (2009) from Jamia Hamdard; MPhil in Bioinformatics (2010) from The Global Open University, Nagaland; and PhD at the Institute of Nuclear Medicine and Allied Sciences (INMAS), DRDO, Delhi in Life Sciences from Bharathiar University, Coimbatore. During his Ph.D., he had designed molecules and evaluated their applications through response modification that regulates stem cells proliferation, differentiation, and apoptosis. His recent research activities are in the field of machine learning, deep learning, and molecular biology, as well as in the development of new scoring function parameterizations for use in docking, simulations, and complex network analysis. Currently, he is working as Scientist ‘D’ in Stem Cell Facility, AIIMS on stem cell informatics to establish a bridge between the experimental science and computational biology.

Affiliations and expertise

BioExIn, Delhi, India

Rajesh Kumar

Dr. Rajesh Kumar Currently he is a postdoctoral fellow at the Developmental Therapeutics Branch of National Cancer Institutes, NIH, USA. His research interest includes immunotherapeutic for cancer and other infectious diseases; analysis of multi-omics data for biomarker identification; understanding genomic structural alterations in cancers; peptide-based therapeutics, developing algorithms for clinical data analysis and interpretation using machine learning for precision medicine. He has published over 25 publications, including international research articles and book chapters. He is a member of the Asia-Pacific Bioinformatics Network society. He was the recipient of CSIR- travel award for delivering the presentation at Gordon research Conference on Genomic Instability and Cancer at Ventura, California USA in 2020. He was also recipient of Carl Storm International Fellowship award in 2020.

Affiliations and expertise

BioExIn, Delhi, India

Anjali Lathwal

Dr. Anjali Lathwal is a researcher in the department of Computational Biology at Indraprastha Institute of Information Technology, Delhi. Her areas of expertise include Applied Machine Learning; Monte-Carlo Simulations; Mathematical Modeling; Computer-aided Vaccine Design; Peptide-based Therapeutics; Cancer Immunotherapy; Biomarkers Discovery; Genomic Annotation & Instability; Survival Modeling; Drug Repurposing; Network Modelling; Database Designing, Management, and Integration. She has published over 10 peer-reviewed publications in renowned international journals, book chapters as a co-author, and done several independent consultancy projects. She is also a member of the Asia-Pacific Bioinformatics Network society and recipient of the Research Excellence Award from the Institute of Scholars. Her research experience shows her substantial contribution to the field of viral therapeutics, biomarker discovery, and computational biology.

Affiliations and expertise

Researcher, Department of Computational Biology, Indraprastha Institute of Information Technology (IIIT), New Delhi, India

Navneet Sharma

Navneet Sharma (M.Pharm, PhD, PGDRA). His work was inclined more towards applied R&D, especially needs-based product development. As an expert in the biomaterials, he had developed dermal decontamination formulation for the radiological decontamination of the skin. He had devised and applied pharmacoscintigraphic procedures for its preclinical evaluation of the drug delivery systems in various experimental models of disease. Further, he had developed the dermal formulations for the broad spectrum decontamination and healing of radiation-induced wounds. For the past five years, his work has been exclusively focused on the Medical Management of Chemical, Biological, Radiological, and Nuclear Emergencies. Currently, He is working in the field of material sciences as a scientist at IIT Delhi.

In his new research carrier of 5 years, he had acclaimed eight national and international awards. The most prominent among them are the SCO and Ministry of External Affairs, Government of India Covid-19 best innovation award 2020, and Department of Science and Technology, Young Scientist Award for the year 2018 and 2022. Currently, he is an investigator in the three projects from DST-India, filled and granted ten patents, four technologies successfully transferred to the industry. He had 45 publications, including five book chapters, authored and edited four books.

Affiliations and expertise

Scientist, Institute of Information Technology (IIT), Delhi, India