Multiobjective Optimization Algorithms for Bioinformatics (eBook)

This book provides an updated and in-depth introduction to the application of multiobjective optimization techniques in bioinformatics. In particular, it presents multiobjective solutions to a range of complex real-world bioinformatics problems. The authors first provide a comprehensive yet concise and self-contained introduction to relevant preliminary methodical constructions such as genetic algorithms, multiobjective optimization, data mining and several challenges in the bioinformatics domain. This is followed by several systematic applications of these techniques to real-world bioinformatics problems in the areas of gene expression and network biology. The book also features detailed theoretical and mathematical notes to facilitate reader comprehension.

The book offers a valuable asset for a broad range of readers - from undergraduate to postgraduate, and as a textbook or reference work. Researchers and professionals can use the book not only to enrich their knowledge of multiobjective optimization and bioinformatics, but also as a comprehensive reference guide to applying and devising novel methods in bioinformatics and related domains.

Dr. Anirban Mukhopadhyay is currently a Professor of the Department of Computer Science and Engineering, University of Kalyani, Kalyani, West Bengal. He obtained his Ph.D. in Computer Science and Engineering from Jadavpur University, Kolkata, India in 2009. He received Erasmus Mundus fellowship in 2009 to carry out post-doctoral research at University of Heidelberg and DKFZ, Heidelberg, Germany during 2009-10. Dr. Mukhopadhyay also worked as visiting professor/scientist at University of Nice Sophia-Antipolis, France, University of Goettingen, Germany (with DAAD scholarship), Colorado State University, USA (with Fulbright-Nehru Fellowship), University of Greifswald, Germany, and University of Lodz, Poland (with Erasmus+ fellowship). He received IEI Young Engineers Award (2013-14) in Computer Engineering Discipline, and INAE Young Engineer Award (2014). He has coauthored two books and about 200 research papers in various International Journals and Conferences. Dr. Mukhopadhyaydelivered invited lectures and served in the Technical Program Committees in many national and international conferences in India and abroad. He is a senior member of IEEE and ACM, and a Fellow of West Bengal Academy of Science and Technology. Dr. Mukhopadhyay received the prestigious Sikhsha Ratna award from Govt. of West Bengal in 2020. He has served as a secretary of IEEE Computational intelligence Society, Kolkata Chapter and currently acts as the Vice-Chair of its Executive Committee. He has successfully guided eleven Ph.D. scholars. His research interests include soft and evolutionary computing, data mining and machine learning, multiobjective optimization, bioinformatics and crowdsourcing. 

Dr. Sumanta Ray is currently an associate professor in the Department of Computer Science and Engineering at Ghani Khan Choudhury Institute of Engineering & Technology (GKCIET), Malda, India. He earned his PhD in Computer Science and Engineering from Jadavpur University in 2017. Dr. Ray received an ERCIM (European Research Consortium for Informatics and Mathematics) grant to pursue postdoctoral research at CENTRUM WISKUNDE and INFORMATICA (CWI), the Netherlands, from 2019 to 2020. He was a recipient of the DST Inspire Fellowship from the Government of India and also received the Senior Research Fellowship from CSIR (Council of Scientific and Industrial Research), MHRD, Government of India. Previously, Dr. Ray served as a Junior Professor at Universität Bielefeld, Bielefeld, Germany, and as an Assistant Professor at the Department of Computer Science and Engineering, Aliah University, Kolkata. He is currently on lien from Aliah University. Dr. Ray has co-authored more than 40 research papers in various journals and conferences. His research interests include bioinformatics, soft and evolutionary computing, multiobjective optimization, deep learning, and pattern recognition. 

Dr. Ujjwal Maulik is a professor in the Department of Computer Science and Engineering, Jadavpur University, Kolkata, India since 2004. He was also the former head of the same Department. He also held the position of the principal in charge and the head of the Department of Computer Science and Engineering, Kalyani Government Engineering College, Kalyani, India. Dr. Maulik has worked in many universities and research laboratories around the world as visiting professor/scientist including Los Alamos National Laboratory, USA; University of New South Wales, Australia; University of Texas at Arlington, USA; University of Maryland at Baltimore County, USA; Fraunhofer Institute for Autonomous Intelligent Systems, St. Augustin, Germany; Tsinghua University, China; Sapienza University, Rome, Italy; University of Heidelberg, Germany; German Cancer Research Center (DKFZ), Germany; Grenoble INP, France; University of Warsaw; University of Padova, Italy; Corvinus University, Budapest; University of Ljubljana, Slovenia; InternationalCenter for Theoretical Physics (ICTP), Trieste, Italy. He is the recipient of Alexander von Humboldt Fellowship during 2010, 2011 and 2012 and Senior Associate of ICTP, Italy during 2012-2018. He is the fellow of Indian National Academy of Engineers (INAE), India, National Academy of Science India (NASI), Asia Pacific Artificial Intelligence Association (AAIA), Singapore, International Association for Pattern Recognition (IAPR), USA and the Institute of Electrical and Electronics Engineers (IEEE), USA. He is also a distinguish member of the ACM. He is distinguish speaker of IEEE as well as ACM. His research interests include machine learning, pattern analysis, data science, bioinformatics, multiobjective optimization, social networking, IoT and autonomous cars. In these areas, he has published ten books, more than four hundred research papers, mentored several start-ups, filed several patents and already guided twenty five doctoral students. His other interest include outdoor sports and classical music. 

Dr. Sanghamitra Bandyopadhyay joined the Machine Intelligence Unit of the Indian Statistical Institute as a faculty member in 1999, after completing her PhD from the same institute. She was the Director of the Institute from August 2015 to July 2020 and is currently on her second tenure as Director from September 2020 onwards. Dr. Bandyopadhyay has worked in various universities and institutes world-wide and has received several awards and fellowships, including the Bhatnagar Prize, Infosys Award, TWAS Prize, JC Bose Fellowship, Swarnajayanti Fellowship and Humboldt Fellowship. She was a senior associate of ICTP and elected Fellow of all Indian National Science and Engineering Academies as well as of IEEE, TWAS and IAPR. Dr. Bandyopadhyay received the prestigious Padma Shri Award from Government of India in 2022. She is currently a member of the Science, Technology and Innovation Advisory Council of the Prime Minister of India (PM-STIAC). The research interests of Prof. Sanghamitra Bandyopadhyay include computational biology and bioinformatics, soft and evolutionary computation, pattern recognition and data mining. She has authored/co-authored more than 300 research article in international journals, conferences and book chapters, and published six authored and edited books. She has also edited journals special issues in the area of soft computing, data mining and bioinformatics.

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This book provides an updated and in-depth introduction to the application of multiobjective optimization techniques in bioinformatics. In particular, it presents multiobjective solutions to a range of complex real-world bioinformatics problems. The authors first provide a comprehensive yet concise and self-contained introduction to relevant preliminary methodical constructions such as genetic algorithms, multiobjective optimization, data mining and several challenges in the bioinformatics domain. This is followed by several systematic applications of these techniques to real-world bioinformatics problems in the areas of gene expression and network biology. The book also features detailed theoretical and mathematical notes to facilitate reader comprehension.The book offers a valuable asset for a broad range of readers from undergraduate to postgraduate, and as a textbook or reference work. Researchers and professionals can use the book not only to enrich their knowledge of multiobjective optimization and bioinformatics, but also as a comprehensive reference guide to applying and devising novel methods in bioinformatics and related domains.