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Author: Wang Guohua
Publisher: Frontiers Media SA
Published: 2022-10-05
Total Pages: 157
ISBN-13: 2889746038
DOWNLOAD EBOOKAuthor: Davide Bacciu
Publisher: World Scientific Publishing Europe Limited
Published: 2021
Total Pages: 0
ISBN-13: 9781800610934
DOWNLOAD EBOOKBiology, medicine and biochemistry have become data-centric fields for which Deep Learning methods are delivering groundbreaking results. Addressing high impact challenges, Deep Learning in Biology and Medicine provides an accessible and organic collection of Deep Learning essays on bioinformatics and medicine. It caters for a wide readership, ranging from machine learning practitioners and data scientists seeking methodological knowledge to address biomedical applications, to life science specialists in search of a gentle reference for advanced data analytics.With contributions from internationally renowned experts, the book covers foundational methodologies in a wide spectrum of life sciences applications, including electronic health record processing, diagnostic imaging, text processing, as well as omics-data processing. This survey of consolidated problems is complemented by a selection of advanced applications, including cheminformatics and biomedical interaction network analysis. A modern and mindful approach to the use of data-driven methodologies in the life sciences also requires careful consideration of the associated societal, ethical, legal and transparency challenges, which are covered in the concluding chapters of this book.
Author: Peter Coveney
Publisher: Oxford University Press, USA
Published: 2014-06
Total Pages: 294
ISBN-13: 0199658188
DOWNLOAD EBOOKComputational Biomedicine unifies the different strands of a broad-ranging subject to demonstrate the power of a tool that has the potential to revolutionise our understanding of the human body, and the therapeutic strategies available to maintain and protect it.
Author: Phoebe A. Rice
Publisher: Royal Society of Chemistry
Published: 2008-05-22
Total Pages: 417
ISBN-13: 0854042725
DOWNLOAD EBOOKThis book provides both in-depth background and up-to-date information in this area. The chapters are organized by general themes and principles, written by experts who illustrate topics with current findings. Topics covered include: - the role of ions and hydration in protein-nucleic acid interactions - transcription factors and combinatorial specificity - indirect readout of DNA sequence - single-stranded nucleic acid binding proteins - nucleic acid junctions and proteins, - RNA protein recognition - recognition of DNA damage. It will be a key reference for both advanced students and established scientists wishing to broaden their horizons.
Author: Debmalya Barh
Publisher: Academic Press
Published: 2017-12-01
Total Pages: 645
ISBN-13: 0128047496
DOWNLOAD EBOOKOmics Technologies and Bio-Engineering: Towards Improving Quality of Life, Volume 1 is a unique reference that brings together multiple perspectives on omics research, providing in-depth analysis and insights from an international team of authors. The book delivers pivotal information that will inform and improve medical and biological research by helping readers gain more direct access to analytic data, an increased understanding on data evaluation, and a comprehensive picture on how to use omics data in molecular biology, biotechnology and human health care. - Covers various aspects of biotechnology and bio-engineering using omics technologies - Focuses on the latest developments in the field, including biofuel technologies - Provides key insights into omics approaches in personalized and precision medicine - Provides a complete picture on how one can utilize omics data in molecular biology, biotechnology and human health care
Author: Rajshree Srivastava
Publisher: Walter de Gruyter GmbH & Co KG
Published: 2020-10-12
Total Pages: 180
ISBN-13: 3110676125
DOWNLOAD EBOOKPredictive Intelligence in Biomedical and Health Informatics focuses on imaging, computer-aided diagnosis and therapy as well as intelligent biomedical image processing and analysis. It develops computational models, methods and tools for biomedical engineering related to computer-aided diagnostics (CAD), computer-aided surgery (CAS), computational anatomy and bioinformatics. Large volumes of complex data are often a key feature of biomedical and engineering problems and computational intelligence helps to address such problems. Practical and validated solutions to hard biomedical and engineering problems can be developed by the applications of neural networks, support vector machines, reservoir computing, evolutionary optimization, biosignal processing, pattern recognition methods and other techniques to address complex problems of the real world.
Author: Alain Goriely
Publisher: Springer
Published: 2017-05-29
Total Pages: 651
ISBN-13: 038787710X
DOWNLOAD EBOOKThis monograph presents a general mathematical theory for biological growth. It provides both a conceptual and a technical foundation for the understanding and analysis of problems arising in biology and physiology. The theory and methods are illustrated on a wide range of examples and applications. A process of extreme complexity, growth plays a fundamental role in many biological processes and is considered to be the hallmark of life itself. Its description has been one of the fundamental problems of life sciences, but until recently, it has not attracted much attention from mathematicians, physicists, and engineers. The author herein presents the first major technical monograph on the problem of growth since D’Arcy Wentworth Thompson’s 1917 book On Growth and Form. The emphasis of the book is on the proper mathematical formulation of growth kinematics and mechanics. Accordingly, the discussion proceeds in order of complexity and the book is divided into five parts. First, a general introduction on the problem of growth from a historical perspective is given. Then, basic concepts are introduced within the context of growth in filamentary structures. These ideas are then generalized to surfaces and membranes and eventually to the general case of volumetric growth. The book concludes with a discussion of open problems and outstanding challenges. Thoughtfully written and richly illustrated to be accessible to readers of varying interests and background, the text will appeal to life scientists, biophysicists, biomedical engineers, and applied mathematicians alike.
Author: Gary B. Fogel
Publisher: John Wiley & Sons
Published: 2007-12-10
Total Pages: 377
ISBN-13: 0470199083
DOWNLOAD EBOOKCombining biology, computer science, mathematics, and statistics, the field of bioinformatics has become a hot new discipline with profound impacts on all aspects of biology and industrial application. Now, Computational Intelligence in Bioinformatics offers an introduction to the topic, covering the most relevant and popular CI methods, while also encouraging the implementation of these methods to readers' research.
Author: Darius M. Dziuda
Publisher: John Wiley & Sons
Published: 2010-07-16
Total Pages: 348
ISBN-13: 0470593407
DOWNLOAD EBOOKData Mining for Genomics and Proteomics uses pragmatic examples and a complete case study to demonstrate step-by-step how biomedical studies can be used to maximize the chance of extracting new and useful biomedical knowledge from data. It is an excellent resource for students and professionals involved with gene or protein expression data in a variety of settings.
Author: Ian Goodfellow
Publisher: MIT Press
Published: 2016-11-10
Total Pages: 801
ISBN-13: 0262337371
DOWNLOAD EBOOKAn introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
