Computational Learning Models And Methods Driven By Omics For Biology For The Fifth China Computer Society Bioinformatics Conference
DOWNLOAD
Download Computational Learning Models And Methods Driven By Omics For Biology For The Fifth China Computer Society Bioinformatics Conference PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Computational Learning Models And Methods Driven By Omics For Biology For The Fifth China Computer Society Bioinformatics Conference book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Computational Learning Models And Methods Driven By Omics For Biology For The Fifth China Computer Society Bioinformatics Conference
DOWNLOAD
Author : Wang Guohua
language : en
Publisher: Frontiers Media SA
Release Date : 2022-10-05
Computational Learning Models And Methods Driven By Omics For Biology For The Fifth China Computer Society Bioinformatics Conference written by Wang Guohua and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-05 with Science categories.
Deep Learning In Biology And Medicine
DOWNLOAD
Author : Davide Bacciu
language : en
Publisher: World Scientific
Release Date : 2022-01-17
Deep Learning In Biology And Medicine written by Davide Bacciu and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-17 with Computers categories.
Biology, 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.
Multivariate Statistical Machine Learning Methods For Genomic Prediction
DOWNLOAD
Author : Osval Antonio Montesinos López
language : en
Publisher: Springer Nature
Release Date : 2022-02-14
Multivariate Statistical Machine Learning Methods For Genomic Prediction written by Osval Antonio Montesinos López and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-14 with Technology & Engineering categories.
This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.
Deep Learning
DOWNLOAD
Author : Ian Goodfellow
language : en
Publisher: MIT Press
Release Date : 2016-11-10
Deep Learning written by Ian Goodfellow and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-10 with Computers categories.
An 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.
Protein Nucleic Acid Interactions
DOWNLOAD
Author : Phoebe A. Rice
language : en
Publisher: Royal Society of Chemistry
Release Date : 2008-05-22
Protein Nucleic Acid Interactions written by Phoebe A. Rice and has been published by Royal Society of Chemistry this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-05-22 with Science categories.
The structural biology of protein-nucleic acid interactions is in some ways a mature field and in others in its infancy. High-resolution structures of protein-DNA complexes have been studied since the mid 1980s and a vast array of such structures has now been determined, but surprising and novel structures still appear quite frequently. High-resolution structures of protein-RNA complexes were relatively rare until the last decade. Propelled by advances in technology as well as the realization of RNA''s importance to biology, the number of example structures has ballooned in recent years. New insights are now being gained from comparative studies only recently made possible due to the size of the database, as well as from careful biochemical and biophysical studies. As a result of the explosion of research in this area, it is no longer possible to write a comprehensive review. Instead, current review articles tend to focus on particular subtopics of interest. This makes it difficult for newcomers to the field to attain a solid understanding of the basics. One goal of this book is therefore to provide in-depth discussions of the fundamental principles of protein-nucleic acid interactions as well as to illustrate those fundamentals with up-to-date and fascinating examples for those who already possess some familiarity with the field. The book also aims to bridge the gap between the DNA- and the RNA- views of nucleic acid - protein recognition, which are often treated as separate fields. However, this is a false dichotomy because protein - DNA and protein - RNA interactions share many general principles. This book therefore includes relevant examples from both sides, and frames discussions of the fundamentals in terms that are relevant to both. The monograph approaches the study of protein-nucleic acid interactions in two distinctive ways. First, DNA-protein and RNA-protein interactions are presented together. Second, the first half of the book develops the principles of protein-nucleic acid recognition, whereas the second half applies these to more specialized topics. Both halves are illustrated with important real life examples. The first half of the book develops fundamental principles necessary to understand function. An introductory chapter by the editors reviews the basics of nucleic acid structure. Jen-Jacobsen and Jacobsen discuss how solvent interactions play an important role in recognition, illustrated with extensive thermodynamic data on restriction enzymes. Marmorstein and Hong introduce the zoology of the DNA binding domains found in transcription factors, and describe the combinational recognition strategies used by many multiprotein eukaryotic complexes. Two chapters discuss indirect readout of DNA sequence in detail: Berman and Lawson explain the basic principles and illustrate them with in-depth studies of CAP, while in their chapter on DNA bending and compaction Johnson, Stella and Heiss highlight the intrinsic connections between DNA bending and indirect readout. Horvath lays out the fundamentals of protein recognition of single stranded DNA and single stranded RNA, and describes how they apply in a detailed analysis of telomere end binding proteins. Nucleic acids adopt more complex structures - Lilley describes the conformational properties of helical junctions, and how proteins recognize and cleave them. Because RNA readily folds due to the stabilizing role of its 2''-hydroxyl groups, Li discusses how proteins recognize different RNA folds, which include duplex RNA. With the fundamentals laid out, discussion turns to more specialized examples taken from important aspects of nucleic acid metabolism. Schroeder discusses how proteins chaperone RNA by rearranging its structure into a functional form. Berger and Dong discuss how topoisomerases alter the topology of DNA and relieve the superhelical tension introduced by other processes such as replication and transcription. Dyda and Hickman show how DNA transposes mediate genetic mobility and Van Duyne discusses how site-specific recombinases "cut" and "paste" DNA. Horton presents a comprehensive review of the structural families and chemical mechanisms of DNA nucleases, whereas Li in her discussion of RNA-protein recognition also covers RNA nucleases. Lastly, FerrÚ-D''AmarÚ shows how proteins recognize and modify RNA transcripts at specific sites. The book also emphasises the impact of structural biology on understanding how proteins interact with nucleic acids and it is intended for advanced students and established scientists wishing to broaden their horizons.
Data Mining In Bioinformatics
DOWNLOAD
Author : Jason T. L. Wang
language : en
Publisher: Springer Science & Business Media
Release Date : 2005
Data Mining In Bioinformatics written by Jason T. L. Wang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Computers categories.
Written especially for computer scientists, all necessary biology is explained. Presents new techniques on gene expression data mining, gene mapping for disease detection, and phylogenetic knowledge discovery.
Crop Improvement
DOWNLOAD
Author : Khalid Rehman Hakeem
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-13
Crop Improvement written by Khalid Rehman Hakeem and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-13 with Science categories.
The improvement of crop species has been a basic pursuit since cultivation began thousands of years ago. To feed an ever increasing world population will require a great increase in food production. Wheat, corn, rice, potato and few others are expected to lead as the most important crops in the world. Enormous efforts are made all over the world to document as well as use these resources. Everybody knows that the introgression of genes in wheat provided the foundation for the “Green Revolution”. Later also demonstrated the great impact that genetic resources have on production. Several factors are contributing to high plant performance under different environmental conditions, therefore an effective and complementary use of all available technological tools and resources is needed to meet the challenge.
Omics Technologies And Bio Engineering
DOWNLOAD
Author : Debmalya Barh
language : en
Publisher: Academic Press
Release Date : 2017-12-01
Omics Technologies And Bio Engineering written by Debmalya Barh and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-01 with Science categories.
Omics 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.
Computational Methods In Systems Biology
DOWNLOAD
Author : Eugenio Cinquemani
language : en
Publisher: Springer Nature
Release Date : 2021-09-13
Computational Methods In Systems Biology written by Eugenio Cinquemani and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-13 with Science categories.
This book constitutes the refereed proceedings of the 19th International Conference on Computational Methods in Systems Biology, CMSB 2021, held in Bordeaux, France, September 22–24, 2021.*The 13 full papers and 5 tool papers were carefully reviewed and selected from 32 submissions. The topics of interest include biological process modelling; biological system model verification, validation, analysis, and simulation; high-performance computational systems biology; model inference from experimental data; multi-scale modeling and analysis methods; computational approaches for synthetic biology; machine learning and data-driven approaches; microbial ecology modelling and analysis; methods and protocols for populations and their variability; models, applications, and case studies in systems and synthetic biology. The chapters "Microbial Community Decision Making Models in Batch", "Population design for synthetic gene circuits", "BioFVM-X: An MPI+OpenMP 3-D Simulator for Biological Systems" are published open access under a CC BY license (Creative Commons Attribution 4.0 International License). * The conference was held in a hybrid mode due to the COVID-19 pandemic.
Practical Applications Of Computational Biology And Bioinformatics 13th International Conference
DOWNLOAD
Author : Florentino Fdez-Riverola
language : en
Publisher: Springer
Release Date : 2019-06-21
Practical Applications Of Computational Biology And Bioinformatics 13th International Conference written by Florentino Fdez-Riverola and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-21 with Technology & Engineering categories.
This book features 21 papers spanning many different sub-fields in bioinformatics and computational biology, presenting the latest research on the practical applications to promote fruitful interactions between young researchers in different areas related to the field. Next-generation sequencing technologies, together with other emerging and diverse experimental techniques, are evolving rapidly, creating numerous types of omics data. These, in turn, are creating new challenges for the expanding fields of bioinformatics and computational biology, which seek to analyse, process, integrate and extract meaningful knowledge from such data. This calls for new algorithms and approaches from fields such as databases, statistics, data mining, machine learning, optimization, computer science, machine learning and artificial intelligence. Clearly, biology is increasingly becoming a science of information, requiring tools from the computational sciences. To address these challenges, we have seen the emergence of a new generation of interdisciplinary scientists with a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific areas is, more than ever, vital to boost the research efforts in the field and contribute to the training of the new generation of interdisciplinary scientists.