[PDF] Computational Life Sciences eBook

Author : Jens Dörpinghaus
Publisher : Springer Nature
Page : 593 pages
File Size : 43,59 MB
Release : 2023-03-04
Category : Computers
ISBN : 303108411X

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This book broadly covers the given spectrum of disciplines in Computational Life Sciences, transforming it into a strong helping hand for teachers, students, practitioners and researchers. In Life Sciences, problem-solving and data analysis often depend on biological expertise combined with technical skills in order to generate, manage and efficiently analyse big data. These technical skills can easily be enhanced by good theoretical foundations, developed from well-chosen practical examples and inspiring new strategies. This is the innovative approach of Computational Life Sciences-Data Engineering and Data Mining for Life Sciences: We present basic concepts, advanced topics and emerging technologies, introduce algorithm design and programming principles, address data mining and knowledge discovery as well as applications arising from real projects. Chapters are largely independent and often flanked by illustrative examples and practical advise.

Author : Angela B. Shiflet
Publisher : Princeton University Press
Page : 857 pages
File Size : 37,44 MB
Release : 2014-03-30
Category : Computers
ISBN : 140085055X

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The essential introduction to computational science—now fully updated and expanded Computational science is an exciting new field at the intersection of the sciences, computer science, and mathematics because much scientific investigation now involves computing as well as theory and experiment. This textbook provides students with a versatile and accessible introduction to the subject. It assumes only a background in high school algebra, enables instructors to follow tailored pathways through the material, and is the only textbook of its kind designed specifically for an introductory course in the computational science and engineering curriculum. While the text itself is generic, an accompanying website offers tutorials and files in a variety of software packages. This fully updated and expanded edition features two new chapters on agent-based simulations and modeling with matrices, ten new project modules, and an additional module on diffusion. Besides increased treatment of high-performance computing and its applications, the book also includes additional quick review questions with answers, exercises, and individual and team projects. The only introductory textbook of its kind—now fully updated and expanded Features two new chapters on agent-based simulations and modeling with matrices Increased coverage of high-performance computing and its applications Includes additional modules, review questions, exercises, and projects An online instructor's manual with exercise answers, selected project solutions, and a test bank and solutions (available only to professors) An online illustration package is available to professors

Author : Benny Chor
Publisher : Cambridge University Press
Page : 219 pages
File Size : 13,38 MB
Release : 2022-09-08
Category : Computers
ISBN : 1107197244

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Computational thinking is increasingly gaining importance in modern biology, due to the unprecedented scale at which data is nowadays produced. Bridging the cultural gap between the biological and computational sciences, this book serves as an accessible introduction to computational concepts for students in the life sciences. It focuses on teaching algorithmic and logical thinking, rather than just the use of existing bioinformatics tools or programming. Topics are presented from a biological point of view, to demonstrate how computational approaches can be used to solve problems in biology such as biological image processing, regulatory networks, and sequence analysis. The book contains a range of pedagogical features to aid understanding, including real-world examples, in-text exercises, end-of-chapter problems, colour-coded Python code, and 'code explained' boxes. User-friendly throughout, Computational Thinking for Life Scientists promotes the thinking skills and self-efficacy required for any modern biologist to adopt computational approaches in their research with confidence.

Author : Cannataro, Mario
Publisher : IGI Global
Page : 960 pages
File Size : 19,18 MB
Release : 2009-05-31
Category : Medical
ISBN : 1605663751

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"This book provides methodologies and developments of grid technologies applied in different fields of life sciences"--Provided by publisher.

Author : Michael R. Berthold
Publisher : Springer Science & Business Media
Page : 279 pages
File Size : 44,28 MB
Release : 2006-09-21
Category : Computers
ISBN : 3540457674

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This book constitutes the refereed proceedings of the Second International Symposium on Computational Life Sciences, CompLife 2006, held in Cambridge, UK, in September 2006.The 25 revised full papers presented were carefully reviewed and selected from 56 initial submissions. The papers are organized in topical sections on genomics, data mining, molecular simulation, molecular informatics, systems biology, biological networks/metabolism, and computational neuroscience.

Author : Kholmirzo Kholmurodov
Publisher : Nova Science Publishers
Page : 0 pages
File Size : 17,69 MB
Release : 2015
Category : Molecular biology
ISBN : 9781634825412

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In this book, original papers have been collected to demonstrate the efficient use of computer molecular dynamics simulation methods for the studying of nanoscale phenomena in the materials and life sciences. This book discusses modern molecular simulation methods for the study of molecular shape and properties in protein and polymer engineering, drugs and materials design, structure-function relationships, and related issues. This book contains the Proceedings of the MSSMBS-2014 and DSCMBS-2014 International Workshops which have been organised by the Joint Institute for Nuclear Research, the Institute of Bioorganic Chemistry of the Russian Academy of Sciences and S.U. Umarov Physical-Technical Institute of the Academy of Sciences of the Republic of Tajikistan. The research topics discussed in the MSSMBS'14 & DSCMBS'14 International Workshops are as follows: computer molecular simulation methods and approaches; molecular dynamics and Monte-Carlo techniques; modelling of biological molecules; physical and biochemical systems; material fabrication and design; drug design in medicine; computational and computing physics, chemistry, biology and medicine; GPU accelerated molecular dynamics and related techniques.

Author : Emmanuel Barillot
Publisher : CRC Press
Page : 463 pages
File Size : 23,39 MB
Release : 2012-08-25
Category : Science
ISBN : 1439831440

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The future of cancer research and the development of new therapeutic strategies rely on our ability to convert biological and clinical questions into mathematical models—integrating our knowledge of tumour progression mechanisms with the tsunami of information brought by high-throughput technologies such as microarrays and next-generation sequencing. Offering promising insights on how to defeat cancer, the emerging field of systems biology captures the complexity of biological phenomena using mathematical and computational tools. Novel Approaches to Fighting Cancer Drawn from the authors’ decade-long work in the cancer computational systems biology laboratory at Institut Curie (Paris, France), Computational Systems Biology of Cancer explains how to apply computational systems biology approaches to cancer research. The authors provide proven techniques and tools for cancer bioinformatics and systems biology research. Effectively Use Algorithmic Methods and Bioinformatics Tools in Real Biological Applications Suitable for readers in both the computational and life sciences, this self-contained guide assumes very limited background in biology, mathematics, and computer science. It explores how computational systems biology can help fight cancer in three essential aspects: Categorising tumours Finding new targets Designing improved and tailored therapeutic strategies Each chapter introduces a problem, presents applicable concepts and state-of-the-art methods, describes existing tools, illustrates applications using real cases, lists publically available data and software, and includes references to further reading. Some chapters also contain exercises. Figures from the text and scripts/data for reproducing a breast cancer data analysis are available at www.cancer-systems-biology.net.

Author : Tuan D. Pham
Publisher : Springer
Page : 221 pages
File Size : 27,53 MB
Release : 2012-12-14
Category : Technology & Engineering
ISBN : 3642330150

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This book presents a sample of research on knowledge-based systems in biomedicine and computational life science. The contributions include: personalized stress diagnosis system, image analysis system for breast cancer diagnosis, analysis of neuronal cell images, structure prediction of protein, relationship between two mental disorders, detection of cardiac abnormalities, holistic medicine based treatment and analysis of life-science data.

Author : Saleh Alkhalifa
Publisher : Packt Publishing Ltd
Page : 408 pages
File Size : 23,33 MB
Release : 2022-01-28
Category : Mathematics
ISBN : 1801815674

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Explore all the tools and templates needed for data scientists to drive success in their biotechnology careers with this comprehensive guide Key FeaturesLearn the applications of machine learning in biotechnology and life science sectorsDiscover exciting real-world applications of deep learning and natural language processingUnderstand the general process of deploying models to cloud platforms such as AWS and GCPBook Description The booming fields of biotechnology and life sciences have seen drastic changes over the last few years. With competition growing in every corner, companies around the globe are looking to data-driven methods such as machine learning to optimize processes and reduce costs. This book helps lab scientists, engineers, and managers to develop a data scientist's mindset by taking a hands-on approach to learning about the applications of machine learning to increase productivity and efficiency in no time. You'll start with a crash course in Python, SQL, and data science to develop and tune sophisticated models from scratch to automate processes and make predictions in the biotechnology and life sciences domain. As you advance, the book covers a number of advanced techniques in machine learning, deep learning, and natural language processing using real-world data. By the end of this machine learning book, you'll be able to build and deploy your own machine learning models to automate processes and make predictions using AWS and GCP. What you will learnGet started with Python programming and Structured Query Language (SQL)Develop a machine learning predictive model from scratch using PythonFine-tune deep learning models to optimize their performance for various tasksFind out how to deploy, evaluate, and monitor a model in the cloudUnderstand how to apply advanced techniques to real-world dataDiscover how to use key deep learning methods such as LSTMs and transformersWho this book is for This book is for data scientists and scientific professionals looking to transcend to the biotechnology domain. Scientific professionals who are already established within the pharmaceutical and biotechnology sectors will find this book useful. A basic understanding of Python programming and beginner-level background in data science conjunction is needed to get the most out of this book.