With the exploration of omics technologies, researchers are able to collect high-throughput biomedical data. The explosion of these new frontier omics technologies produces diverse genomic datasets such as microarray gene expression, miRNA expression, DNA sequence, 3D structures etc. These different representations (modality) of the biomedical data contain distinct, useful and complementary information of different samples. As a consequence, there is a growing interest in collecting ”multi-modal” data for the same set of subjects and integrating this heterogeneous information to obtain more profound insights into the underlying biological system. The current tutorial will discuss in detail different problems of bioinformatics and the concepts of multimodality in bioinformatics. In recent years different machine learning and deep learning based approaches become popular in dealing with multimodal data. A detailed discussion along this direction will also be presented in the tutorial. This tutorial will be an advanced survey equally of interest to academic researchers and industry practitioners - very timely with so much vibrant research in the computational biology domain over the past 5 years.Time and location: To Be Announced.
Dr. Sriparna Saha research interests include machine learning, multi-objective optimization, evolutionary techniques, text mining and biomedical information extraction. She is the recipient of the Google India Women in Engineering Award, 2008, NASI YOUNG SCIENTIST PLATINUM JUBILEE AWARD 2016, BIRD Award 2016, IEI Young Engineers’ Award 2016, Humboldt Research Fellowship 2016, Indo-U.S. Fellowship for Women in STEMM (WISTEMM) Women Overseas Fellowship program 2018, SERB WOMEN IN EXCELLENCE AWARD 2018, SERB Early Career Research Award 2018, DUO-India fellowship 2020, and CNRS fellowship. She has published papers on those topics in reputed fora like IEEE/ACM Transactions on Computational Biology and Bioinformatics, IEEE Intelligent Systems, IEEE Computational Intelligence Magazine, Scientific Reports, ACM Transactions on Knowledge Discovery from Data, ECIR and many more.
Mr. Pratik Dutta received his BE and ME degree from Indian Institute of Engineering Science and Technology, Shibpur in 2013 and 2015, respectively. His research interest lies in computational biology, genomic sequence, protein-protein interaction, machine learning and deep learning techniques. He has published various research articles in different prestigious fora like Elsevier Computers in Biology and Medicine, IEEE/ACM Transactions on Computational Biology and Bioinformatics, IEEE Journal of Biomedical and Health Informatics, IEEE Congress on Evolutionary Computation, Scientific Reports,