{"product_id":"genomics-at-the-nexus-of-ai-computer-vision-and-machine-learning-hardback-9781394268801","title":"Genomics at the Nexus of AI, Computer Vision, and Machine Learning (Hardback) 9781394268801","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eGenomics at the Nexus of AI, Computer Vision, and Machine Learning\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cfont size=\"4\"\u003eShilpa Choudhary (Edited by), S Choudhary (Author), Sandeep Kumar (Edited by), Swathi Gowroju (Edited by), Monali Gulhane (Edited by), R. Sri Lakshmi (Edited by)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781394268801, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 22 December 2024\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e560 pages\u003cbr\u003e25 x 15 x 1.5 cm, 0.454 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\u003cb\u003eThe book provides a comprehensive understanding of cutting-edge research and applications at the intersection of genomics and advanced AI techniques and serves as an essential resource for researchers, bioinformaticians, and practitioners looking to leverage genomics data for AI-driven insights and innovations.\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eThe book encompasses a wide range of topics, starting with an introduction to genomics data and its unique characteristics. Each chapter unfolds a unique facet, delving into the collaborative potential and challenges that arise from advanced technologies. It explores image analysis techniques specifically tailored for genomic data. It also delves into deep learning showcasing the power of convolutional neural networks (CNN) and recurrent neural networks (RNN) in genomic image analysis and sequence analysis. Readers will gain practical knowledge on how to apply deep learning techniques to unlock patterns and relationships in genomics data. Transfer learning, a popular technique in AI, is explored in the context of genomics, demonstrating how knowledge from pre-trained models can be effectively transferred to genomic datasets, leading to improved performance and efficiency. Also covered is the domain adaptation techniques specifically tailored for genomics data. The book explores how genomics principles can inspire the design of AI algorithms, including genetic algorithms, evolutionary computing, and genetic programming. Additional chapters delve into the interpretation of genomic data using AI and ML models, including techniques for feature importance and visualization, as well as explainable AI methods that aid in understanding the inner workings of the models. The applications of genomics in AI span various domains, and the book explores AI-driven drug discovery and personalized medicine, genomic data analysis for disease diagnosis and prognosis, and the advancement of AI-enabled genomic research. Lastly, the book addresses the ethical considerations in integrating genomics with AI, computer vision, and machine learning. \u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eAudience\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eThe book will appeal to biomedical and computer\/data scientists and researchers working in genomics and bioinformatics seeking to leverage AI, computer vision, and machine learning for enhanced analysis and discovery; healthcare professionals advancing personalized medicine and patient care; industry leaders and decision-makers in biotechnology, pharmaceuticals, and healthcare industries seeking strategic insights into the integration of genomics and advanced technologies.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003ePreface xvii \u003cp\u003e1 Integrating Genomics and Computer Vision: Unravelling Genetic Patterns and Analyzing Genomic Data 1 \u003cbr\u003e \u003ci\u003eNeha Tanwar, Sandeep Kumar, Garima Singh and Monika Bhakta\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2 Syndrome Detection Unleashed: Computer Vision Applications in Neurogenetic Diagnoses 25\u003cbr\u003e \u003ci\u003eR. Srilakshmi, Shilpa Choudhary, Rohit Raja and Ashish Kumar Luhach\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3 Integrating Machine Learning for Personalized Kidney Stone Risk Assessment: A Prospective Validation Using CLDN11 Genetic Data and Clinical Factors 59\u003cbr\u003e \u003ci\u003eShilpa Choudhary, Monali Gulhane, Sandeep Kumar, Nitin Rakesh, Sudhanshu Maurya and Chanderdeep Tandon\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4 Unravelling the Complexities of Genetic Codes Through Advanced Machine Learning Algorithms for DNA Sequencing and Analysis 87\u003cbr\u003e \u003ci\u003eSwathi Gowroju, Mandeep Kumar, Sharvin Vats, Pramadvara Kushwaha and Rohit Raja\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5 Deciphering the Complexities of Breast Cancer: Unveiling Resistance Mechanisms 109\u003cbr\u003e \u003ci\u003eMaddula Pallavi, Chirandas Tejaswi, R. Srilakshmi and Chetan Swarup\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6 Deciphering the Genetic Terrain: Identifying Genetic Variants in Uncommon Disorders with Pathogenic Effects 133\u003cbr\u003e \u003ci\u003eNikhila Kathirisetty, Ravula Arun Kumar, G. Suryanarayana, Farhana Begum, C. Padmini and Pravin Tirgar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7 Genome Data-Based Explainable Recommender Systems: A State-of-the-Art Survey 149\u003cbr\u003e \u003ci\u003eV. Lakshmi Chetana and Hari Seetha\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8 Optimizing TCGA Data Analysis: Unveiling Crucial Cancer-Related Gene Alterations Through a Fusion Approach QL Gradient 169\u003cbr\u003e \u003ci\u003eSushma Chowdary Polavarapu, Sri Hari Nallamala, Sudheer Mangalampalli, Brahma Naidu Nalluri, Lalitha Rajeswari Burra and Swarna Lalitha Chukka\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9 Leveraging Deep Learning for Genomics Analysis: Advances and Applications 191\u003cbr\u003e \u003ci\u003eNisarg Gandhewar, Amit Pimpalkar, Anuja Jadhav, Nilesh Shelke and Rashmi Jain\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10 Unraveling Biological Complexity: Leveraging Deep Learning Models for Precise Classification and Understanding of Protein Types and Functions 227\u003cbr\u003e \u003ci\u003eSwathi Gowroju, M. Sudhakar, Mohit and Turki Aljrees\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11 The Impact of Learning Techniques on Genomics: Revolutionizing Research and Clinical Breast Cancer Application 251\u003cbr\u003e \u003ci\u003eSumaiya Shaikh, G. Suryanarayana, ShaistaFarhat and LNC Prakash K.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12 Comparison of Machine Learning and Deep Learning Algorithms for Diabetes Prediction Using DNA Sequences 269\u003cbr\u003e \u003ci\u003eGagandeep Kaur, Poorva Agrawal, Latika Pinjarkar, Rutuja Patil, Suhashini Chaurasia and Seema Patil\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13 AI Applications in Analyzing Gene Expression for Cancer Diagnosis: A Comprehensive Review 285\u003cbr\u003e \u003ci\u003ePoorva Agrawal, Gagandeep Kaur, Vansh Gupta, Kruthika Agarwal, Latika Pinjarkar and Seema Patil\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14 Optimum Detection of Human Genome Related to Cancer Cells Using Signal Processing 309 \u003cbr\u003e \u003ci\u003eManoranjan Dash and Ritesh Raj\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15 Genomics-Driven Strategies for Sustainable Crop Improvement in Agriculture 321\u003cbr\u003e \u003ci\u003eMunish Kumar, Monika Kajal, Mandeep Kumar, Ramesh Kumar and Pramadvara Kushwaha\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16 An Efficient Deep Convolutional Neural Networks Model for Genomic Sequence Classification 345\u003cbr\u003e \u003ci\u003eAmit Pimpalkar, Nisarg Gandhewar, Nilesh Shelke, Sachin Patil and Sharda Chhabria\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17 Navigating the Genetic Tapestry Using Genetic Analysis on the SLC26A1 Gene Variants in the Detection and Understanding of Kidney Stones for Improved Global Healthcare Management 377\u003cbr\u003e \u003ci\u003eSandeep Kumar, Monali Gulhane, Nitin Rakesh, Sudhanshu Maurya, Rajni Mohana and Chanderdeep Tandon\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18 A Comprehensive Approach for Enhancing Kidney Disease Detection Using Random Forest and Gradient Boosting 395\u003cbr\u003e \u003ci\u003eMandeep Kumar, Neerav Khare, Soumya Mani, Monika Bhaktaand Gaurab Saha\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e19 Decoding the Future: COVID-19 RNA Sequence Prediction Through LSTM Transformation 417\u003cbr\u003e \u003ci\u003eM.D. Khaja Shaik, K. Narsimhulu, B.V.N. Praveena,Sarita Dabur and G. Pratyusha\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e20 Genomics and Machine Learning: ML Approaches, Future Directions and Challenges in Genomics 437\u003cbr\u003e \u003ci\u003eSunita Gupta, Neha Janu, Meenakshi Nawal and Anjali Goswami\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e21 Predicting Gene Ontology Annotations from CAFA Using Distance Machine Learning and Transfer Metric Learning 459\u003cbr\u003e \u003ci\u003eShilpa Choudhary, MD Khaja Shaik, Sivaneasan Bala Krishnan and Sunita Gupta\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e22 PacMan-RL: A Game-Changing Approach to Drug Development Through Reinforcement Learning 483\u003cbr\u003e \u003ci\u003eAbhishek Goud Amkamgari, Harshita Sharma, Rashmi Verma and Bhawna Kaliraman\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e23 Genetic Variant Classification Through Decision Tree Analysis for Enhanced Genomic Understanding 505\u003cbr\u003e \u003ci\u003ePrachi Chaudhary and Rajni Mehra\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIndex 529\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Computer science [\u003ca title=\"See our other books on Computer science\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Computer%20science%20%5BUY%5D%22\"\u003eUY\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-Scrivener","offers":[{"title":"Brand New","offer_id":52433242456344,"sku":"9781394268801","price":182.45,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781394268801.jpg?v=1784852898","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/genomics-at-the-nexus-of-ai-computer-vision-and-machine-learning-hardback-9781394268801","provider":"Freshly Printed Books","version":"1.0","type":"link"}