1st Edition

Machine Learning and IoT A Biological Perspective

Edited By Shampa Sen, Leonid Datta, Sayak Mitra Copyright 2019
    374 Pages 134 B/W Illustrations
    by CRC Press

    This book discusses some of the innumerable ways in which computational methods can be used to facilitate research in biology and medicine - from storing enormous amounts of biological data to solving complex biological problems and enhancing treatment of various grave diseases.

    Machine Learning: A Powerful Tool for Biologists
    Mohd Zafar, Ramkumar Lakshmi Narayanan, Saroj K. Meher, and Shishir K. Behera

    Mining and Analysis of Bioprocess Data
    Prerna Grover, Aditya Shah, and Shampa Sen

    Data Mining in Nutrigenomics
    Avipsha Sarkar, Shreyasi Kundu, Shakti Singh, and Shampa Sen

    Machine Learning in Metabolic Engineering
    Sayak Mitra

    Big Data and Transcriptomics
    Sudharsana Sundarrajan, Sajitha Lulu, and Mohanapriya Arumugam

    Comparative Study of Predictive Models in Microbial-Induced
    Corrosion
    Nitu Joseph and Debayan Mandal

    Application of Data Mining Techniques in Autoimmune Diseases Research and Treatment
    Sweta Bhattacharya and Sombuddha Sengupta

    Data Mining Techniques in Imaging of Embryogenesis
    Diptesh Mahajan and Gaurav K. Verma

    Machine Learning Approach to Overcome the Challenges in Theranostics: A Review
    Bishwambhar Mishra, Sayak Mitra, Karthikeya Srinivasa Varma Gottimukkala, and Shampa Sen

    Emotion Detection System
    Adrish Bhattacharya, Vibhash Chandra, and Leonid Datta

    Segmentation and Clinical Outcome Prediction in Brain Lesions
    Sharmila Nageswaran, S. Vidhya, and Deepa Madathil

    Machine Learning Based Hospital-Acquired Infection Control System
    Prajit Kumar Datta, Sehaj Sharma, and Gaurav Bansal

    No Human Doctor: Learning of the Machine
    Leonid Datta, Emilee Datta, and Shampa Sen

    The IoT Revolution
    Adrish Bhattacharya and Denim Datta

    Healthcare IoT (H-IoT): Applications and Ethical Concerns
    Srijita Banerjee, Adrish Bhattacharya, and Shampa Sen

    Brain–Computer Interface
    Abhishek Mukherjee, Madhurima Gupta, and Shampa Sen

    IoT-Based Wearable Medical Devices
    Avitaj Mitra, Abanish Roy, Harshit Nanda, Riddhi Srivastava, and M. Gayathri

    People with Disabilities: The Helping Hand of IoT
    Ashmita Das, Sayak Mitra, and Shampa Sen

    Smart Analytical Lab
    Subhrodeep Saha, Sourish Sen, Bharti Singh, and Shampa Sen

    Crop and Animal Farming IoT (CAF-IoT)
    Neha Agnihotri, Soumyadipto Santra, and Shampa Sen

    Index

    Biography

    Dr. Shampa Sen is currently working as an Associate Professor at School of Bio-Sciences and Technology, VIT University, Vellore, India. She has more than 57 publications in Environmental Biotechnology, Bionanotechnology and Nutraceuticals.  Dr. Shampa was the Co-PI for project 'Chemisorption-biodecomposition of long resistant pharmaceutical using superparamagentic nanoparticles' funded by NRF-SAVI, Korea. She was actively involved in many professional development activities. Her research interest include biosynthesis of metallic nanoparticles, applications of nanoparticles in biomedical and environmental applications. Recently, she has also tried her hands at machine learning, internet of things and their applications in biology. She has already had a publication in this yet to be explored field regarding computational modeling for evolution of hsp90a homologues, and is currently working on in silico improvement of plant strains using machine learning. She is a life member of Biotech Research Society, India (BRSI) and Environmental Mutagen Society of India (EMSI) and member of International Neural Network Society (INNS).

    Leonid Datta has completed his B.Tech degree in computer science and engineering from VIT University, Vellore, India. He is a student member of INNS, USA. He has a publication in the field of bioinformatics on how the evolution of HSP90A homologues can be modelled computationally. Currently he is working on in silico improvement of plant strains using machine learning. His book chapter on “Application of MapReduce in Parallel Processing Data” and his research work on automation of machine learning algorithms, especially in big data analysis, are currently in the pipeline to get published. His most notable project works include designing truncation techniques for a search engine, developing a system that runs based on RFID scanning for attendance purposes or maintaining other records, and automating the processing of big data through development of a portal.

    Sayak Mitra is currently pursuing his B.Tech degree in Biotechnology at VIT University, Vellore, India. He has recently published articles on environmental nanoremediation, nanobiotechnology, in silico characterisation and synthesis of a lead compound to target a novel receptor as part of cancer therapeutics, and is currently working on metabolic engineering and optimisation procedures for industrial production of certain metabolites. He has also completed projects on detailed structural analysis and evolutionary history of an industrially important protein, bioremoval of manganese by biofilms developed from indigenous bacterial communities of tannery sludge, and many more.