Harnessing Artificial Intelligence-Enhanced Graph Models for Biological Discovery: Unveiling Biological Frontiers introduces revolutionary techniques that merge artificial intelligence with graph-based methods to uncover complex biological networks. Through detailed examples and case studies, the book provides researchers and practitioners the essential tools to analyze molecular interactions, identify key biomarkers, and hasten the discovery of novel therapeutics. Chapters delve into the sophisticated interplay between advanced AI techniques and graph models, specially designed to decode the intricacies of biological systems. By utilizing cutting-edge AI algorithms, readers can explore complex biological networks, forecast molecular interactions, and pinpoint new drug targets with exceptional precision.
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With 24+ years of combined experience in teaching, research, and industry, Prof. Sudan Jha is a Senior Member of IEEE and a Professor in the Department of Computer Science & Engineering at Kathmandu University, Nepal. He leads the IoT R&D Lab at Kathmandu University and has previously been affiliated with KIIT University, Chandigarh University, Christ University, and more. He has held key positions such as Technical Director at Nepal Television, Principal in engineering colleges, and Individual Consultant at Nepal Telecom Authority.
Prof. Jha is an AI expert with active contributions to Nepal's AI Policy 2081 for the Government of Nepal. He has also mentored the AI Concept Paper submitted by the Federation of Computer Association of Nepal (CAN Federation). Additionally, he serves as the Vice President of npCERT (Information Security Response Team Nepal), playing a crucial role in cybersecurity and digital infrastructure initiatives.
Dedicated to advancing higher education and smart platform technologies, he has published 95+ SCI/SCIE-indexed research papers and book chapters in international peer-reviewed journals and conferences. He is a Co-Editor-in-Chief of an international journal and a Guest Editor for SCIE/ESCI/SCOPUS-indexed journals. His research contributions include three patents and authorship/editorship of seven books on IoT, 5G, and AI, published by Elsevier, CRC, and AAP. His work has also secured funding for two international projects.
Prof. Jha has delivered keynote speeches at over 45 international conferences and has conducted faculty development programs, short-term training programs, and workshops at both national and international levels. He holds certifications in Microservices Architecture, Data Science, and Foundations of Artificial Intelligence.
His primary research interests include AI & IoT integration, Quality of Services in IoT-enabled devices, Neutrosophic Theory, and Neutrosophic Soft Set Systems.
Dr. Subhendu kumar Pani received his Ph.D. from Utkal University, Odisha, India. He is working as professor at Krupajal Engineeing College under BPUT, Odisha, India. He has almost 2 decades of teaching and research experience. His research interests include Data mining, Big Data Analysis, web data analytics, Fuzzy Decision Making and Computational Intelligence. He is the recipient of 5 researcher awards. He has published dozens of international journal papers. His professional activities include roles as Book Series Editor, Associate Editor, Editorial board member and/or reviewer of various international journals. He is Associated with a number of conference societies. He has more than 150 international publications, 5 authored books, 15 edited and upcoming books; 20 book chapters into his account. He is a fellow in SSARSC and life member in IE, ISTE, ISCA, OBA.OMS, SMIACSIT, SMUACEE, CSI.
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Paperback. Etat : new. Paperback. Harnessing Artificial Intelligence-Enhanced Graph Models for Biological Discovery: Unveiling Biological Frontiers introduces revolutionary techniques that merge artificial intelligence with graph-based methods to uncover complex biological networks. Through detailed examples and case studies, the book provides researchers and practitioners the essential tools to analyze molecular interactions, identify key biomarkers, and hasten the discovery of novel therapeutics. Chapters delve into the sophisticated interplay between advanced AI techniques and graph models, specially designed to decode the intricacies of biological systems. By utilizing cutting-edge AI algorithms, readers can explore complex biological networks, forecast molecular interactions, and pinpoint new drug targets with exceptional precision. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9780443276088
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