Table Of Content

Applications of Machine Learning and Deep Learning on Biological Data The automated learning of machines characterizes machine learning (ML). It focuses on making data-driven predictions using programmed algorithms. ML has several applications, including bioinformatics, which is a discipline of study and practice that deals with applying computational derivations to obtain biological data. It involves the collection, retrieval, storage, manipulation, and modeling of data for analysis or prediction made using customized software. Previously, com- prehensive programming of bioinformatical algorithms was an extremely laborious task for such applications as predicting protein structures. Now, algorithms using ML and deep learning (DL) have increased the speed and efficacy of programming such algorithms. Applications of Machine Learning and Deep Learning on Biological Data is a study of applying ML and DL techniques to biological areas such as proteomics, genomics, microarrays, text mining, and systems biology. The key objective is to cover ML applications to biological science problems, focusing on problems related to bioinformatics. The book looks at cutting-edge research topics and methodologies in ML applied to the rapidly advancing discipline of bioinformatics. ML and DL applied to biological and neuroimaging data can open new frontiers for biomedical engineering, such as refining the understanding of complex diseases, including cancer and neurodegenerative and psychiatric disorders. Advances in this field could eventually lead to the development of precision medicine and automated diagnostic tools capable of tailoring medical treatments to individual lifestyles, vari- ability, and the environment. Highlights include: ◾ Artificial Intelligence for treating and diagnosing schizophrenia ◾ An analysis of ML and DL’s financial effect on healthcare ◾ An XGBoost-based classification method for breast cancer classification ◾ Using ML to predict squamous diseases ◾ ML and DL applications in genomics and proteomics ◾ Applying ML and DL to biological data Advances in Computational Collective Intelligence Applications of Machine Learning and Deep Learning on Biological Data Edited by Faheem Masoodi, Mohammad Quasim, Syed Nisar Hussain Bukhari, Sarvottam Dixit, and Shadab Alam First edition published 2023 by CRC Press 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742 and by CRC Press 4 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN CRC Press is an imprint of Taylor & Francis Group, LLC © 2023 Taylor & Francis Group, LLC Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. 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For works that are not available on CCC please contact [email protected] Trademark Notice: Product or corporate names may be trademarks or registered trademarks and are used only for identification and explanation without intent to infringe. ISBN: 978-1-032-21437-5 (hbk) ISBN: 978-1-032-35826-0 (pbk) ISBN: 978-1-003-32878-0 (ebk) DOI: 10.1201/9781003328780 Typeset in Adobe Garamond by KnowledgeWorks Global Ltd. Contents Contributors ..................................................................................................vii About the Authors ..........................................................................................ix 1 Deep Learning Approaches, Algorithms, and Applications in Bioinformatics ....................................................................................1 SAAHIRA BANU AHAMED, SHERMIN SHAMSUDHEEN, AND AWATEF SALEM BALOBAID 2 Role of Artificial Intelligence and Machine Learning in Schizophrenia—A Survey ................................................................21 BHAWANA PALIWAL AND KHANDAKAR F. RAHMAN 3 Understanding Financial Impact of Machine and Deep Learning in Healthcare: An Analysis ..........................................41 DR. KHURSHID ALI GANAI AND DR. BILAL AHMAD PANDOW 4 Face Mask Detection Alert System for COVID Prevention Using Deep Learning .........................................................57 PARTH AGARWAL, DHRUV RASTOGI, AND AMAN SHARMA 5 An XGBoost‑Based Classification Method to Classify Breast Cancer .......................................................................................75 DR. KISHWAR SADAF, DR. JABEEN SULTANA, AND NAZIA AHMAD 6 Prediction of Erythemato‑Squamous Diseases Using Machine Learning ......................................................................87 SYED NISAR HUSSAIN BUKHARI, FAHEEM MASOODI, MUNEER AHMAD DAR, NISAR IQBAL WANI, ADFAR SAJAD, AND GOUSIYA HUSSAIN 7 Grouping of Mushroom 5.8s rRNA Sequences by Implementing Hierarchical Clustering Algorithm ...............................97 P. SUDHASINI AND DR. B. ASHADEVI v vi ◾ Contents 8 Applications of Machine Learning and Deep Learning in Genomics and Proteomics ..............................................................113 QURAT-UL-AIN AND UZMA HAMEED 9 Artificial Intelligence: For Biological Data ........................................135 IFRA ALTAF, MUHEET AHMED BUTT AND MAJID ZAMAN 10 Application of ML and DL on Biological Data ..................................159 TAWSEEF AHMED TELI, FAHEEM SYED MASOODI, AND ZUBAIR MASOODI 11 Deep Learning for Bioinformatics .....................................................181 TAWSEEF AHMED TELI AND RAMEEZ YOUSUF Index ...........................................................................................................197 Contributors Nazia Ahmad Syed Nisar Hussain Bukhari Department of Computer Sciences NIELIT Srinagar Applied College Imam Abdul Rahman Jammu and Kashmir, India Bin Faisal University Damam, Kingdom of Saudi Arabia Muheet Ahmad Butt Department of Computer Sciences Saahira Banu Ahamed University of Kashmir Department of Computer Science Jammu and Kashmir, India College of Computer Science and Information Technology Muneer Ahmad Dar Jizan University NIELIT Srinagar Jizan, Kingdom of Saudi Arabia Jammu and Kashmir, India Ifra Altaf Khurshid Ali Ganai Department of Computer Sciences Higher College of Technology University of Kashmir Abu Dhabi, Dubai, United Arab Emirates Jammu and Kashmir, India Uzma Hameed B. Ashadevi Department of Higher Education Department of Computer Sciences Jammu and Kashmir, India M. B. Muthaih, Govt. Arts College for Women Gousiya Hussain Tamil Nadu, India Department of Computer Sciences Mewar University Awatef Salem Balobaid Rajasthan, India Department of Computer Science College of Computer Science and Faheem Syeed Masoodi Information Technology Department of Computer Sciences Jizan University University of Kashmir Jizan, Kingdom of Saudi Arabia Jammu and Kashmir, India vii viii ◾ Contents Zubair Masoodi Aman Sharma Department of Higher Education Department of CS/IT Jammu and Kashmir, India Jaypee University of Information Technology Bhawana Paliwal Himachal Pradesh, India Department of Bio Science and Bio Technology P. Sudhasini Banasthali Vidyapeth Department of Computer Sciences Rajasthan, India Lady Doak College Madhuria Tamil Nadu, India Bilal Ahmad Pandow Center for Career Planning and Jabeen Sultana Counselling Department of Computer Science University of Kashmir College of Computer and Information Jammu and Kashmir, India Science Majmaah University Qurat‑ul‑ain Al Majma’ah, Kingdom of Saudi Department of Higher Education Arabia Jammu and Kashmir, India Tawseef Ahmed Teli Khandakar Faridar Rahman Department of Higher Education Department of Computer Sciences Jammu and Kashmir, India Banasthali Vidyapeth Rajasthan, India Nisar Iqbal Wani Department of Higher Education Kishwar Sadaf Jammu and Kashmir, India Department of Computer Science College of Computer and Information Rameez Yousuf Science Department of Computer Sciences Majmaah University University of Kashmir Al Majma’ah, Kingdom of Saudi Arabia Jammu and Kashmir, India Adfar Sajad Majid Zaman Department of Information Technology Department of IT and SS Cluster University University of Kashmir Jammu and Kashmir, India Jammu and Kashmir, India Shermin Shamsudheen Department of Computer Science College of Computer Science and Information Technology Jizan University Jizan, Kingdom of Saudi Arabia About the Authors Dr. Faheem Syeed Masoodi is an assistant professor in the Department of Computer Science, University of Kashmir, Jammu and Kashmir, India. Earlier, he served the College of Computer Science, University of Jizan, Kingdom of Saudi Arabia, as an assistant professor. Prior, the author served as a research scientist at NMEICT – Edrp project sponsored by the Ministry of HRD, Govt. of India. He was awarded PhD in the domain of Network Security & Cryptography by the Department of Computer Science, Aligarh Muslim University, Aligarh, Uttar Pradesh, India, in the year 2014. He has completed his Masters in Computer Science from University of Kashmir, Jammu and Kashmir, India. His core research interests include cryptography & network security and Internet of things (IOT). He is a professional mem- ber of many cryptology Associations and has published multiple research papers in reputed journals and conferences. He has been awarded fellowship for summer training “Conference effective moduli spaces and application to cryptography organized by CENTRE HENRI LEBESGUE, Rennes, France in 2014, and was also awarded fellowship for summer school SP-ASCRYPTO-2011 Advance School of Cryptography at University of Campinas, Sao Paulo, Brazil, in 2011. He was also awarded Maulana Azad National Fellowship for his doctorate programme by UGC New Delhi. Dr. Mohammad Tabrez Quasim is assistant professor at University of Bisha, Kingdom of Saudi Arabia. Dr. Syed Nisar Hussain Bukhari is working as a Scientist-C at the National Institute of Electronics and Information Technology (NIELIT), Srinagar, Jammu and Kashmir, India. Prof. Sarvottam Dixit holds the post of vice-chancellor, Mewar University, Ghaziabad, Uttar Pradesh, India. Dr. Shadab Alam is an assistant professor in the Department of Computer Science, Jazan University, Jazan, Kingdom of Saudi Arabia. ix