{"product_id":"applications-of-machine-learning-and-deep-learning-on-biological-data-9781032358260","title":"Applications of Machine Learning and Deep Learning on Biological Data","description":"\u003cp\u003e • Author(s): Faheem Masoodi\u003cbr\u003e • Publisher: Taylor \u0026amp; Francis\u003cbr\u003e • Publisher Imprint: Auerbach Publications\u003cbr\u003e • BISAC: Artificial Intelligence - General\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThe 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, comprehensive 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.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eApplications of Machine Learning and Deep Learning on Biological Data\u003c\/strong\u003e is an examination of applying ML and DL to such areas 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. \u003c\/p\u003e\u003cp\u003eML 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, variability, and the environment.\u003c\/p\u003e\u003cp\u003eHighlights include: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eArtificial Intelligence in treating and diagnosing schizophrenia\u003c\/li\u003e \u003cli\u003eAn analysis of ML's and DL's financial effect on healthcare\u003c\/li\u003e \u003cli\u003eAn XGBoost-based classification method for breast cancer classification\u003c\/li\u003e \u003cli\u003eUsing ML to predict squamous diseases\u003c\/li\u003e \u003cli\u003eML and DL applications in genomics and proteomics\u003c\/li\u003e \u003cli\u003eApplying ML and DL to biological data\u003c\/li\u003e \u003c\/ul\u003e","brand":"Taylor \u0026 Francis","offers":[{"title":"Paperback","offer_id":45243481981079,"sku":"9781032358260","price":4021.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9781032358260.webp?v=1769234888","url":"https:\/\/atlanticbooks.com\/products\/applications-of-machine-learning-and-deep-learning-on-biological-data-9781032358260","provider":"Atlantic Books","version":"1.0","type":"link"}