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Author: Michael Berthold
Publisher: Springer Science & Business Media
ISBN: 3540291040
Category : Bioinformatics
Languages : en
Pages : 287
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Book Description
Author: Michael Berthold
Publisher: Springer Science & Business Media
ISBN: 3540291040
Category : Bioinformatics
Languages : en
Pages : 287
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Book Description
Author: Jens Dörpinghaus
Publisher: Springer Nature
ISBN: 303108411X
Category : Computers
Languages : en
Pages : 593
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Book Description
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: Cannataro, Mario
Publisher: IGI Global
ISBN: 1605663751
Category : Medical
Languages : en
Pages : 960
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Book Description
"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
ISBN: 3540457682
Category : Science
Languages : en
Pages : 279
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Book Description
This book constitutes the refereed proceedings of the Second International Symposium on Computational Life Sciences, CompLife 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: Tuan D. Pham
Publisher: Springer
ISBN: 3642330150
Category : Technology & Engineering
Languages : en
Pages : 221
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Book Description
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
ISBN: 1801815674
Category : Mathematics
Languages : en
Pages : 408
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Book Description
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.
Author: R. Heijungs
Publisher: Springer Science & Business Media
ISBN: 9401599009
Category : Science
Languages : en
Pages : 247
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Book Description
Life Cycle assessment (LCA) is a tool for environmental decision-support in relation to products from the cradle to the grave. Until now, more emphasis has been put on the inclusion quantitative models and databases and on the design of guidebooks for applying LCA than on the integrative aspect of combining these models and data. This is a remarkable thing, since LCA in practice deals with thousands of quantitative data items that have to be combined in the correct manner. For this, one needs mathematical rules and algorithmic principles for carrying out an LCA. This book presents the first coherent treatment of the mathematical and algorithmic aspects of LCA. These computational aspects are presented in matrix form, so that a concise and elegant formulation is achieved. This form, moreover, provides a platform for further extension of analysis using perturbation theory, structural theory and economic input-output analysis.
Author: Alexander Lancaster
Publisher: Apress
ISBN: 1484245237
Category : Computers
Languages : en
Pages : 396
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Book Description
Treat yourself to a lively, intuitive, and easy-to-follow introduction to computer programming in Python. The book was written specifically for biologists with little or no prior experience of writing code - with the goal of giving them not only a foundation in Python programming, but also the confidence and inspiration to start using Python in their own research. Virtually all of the examples in the book are drawn from across a wide spectrum of life science research, from simple biochemical calculations and sequence analysis, to modeling the dynamic interactions of genes and proteins in cells, or the drift of genes in an evolving population. Best of all, Python for the Life Sciences shows you how to implement all of these projects in Python, one of the most popular programming languages for scientific computing. If you are a life scientist interested in learning Python to jump-start your research, this is the book for you. What You'll Learn Write Python scripts to automate your lab calculations Search for important motifs in genome sequences Use object-oriented programming with Python Study mining interaction network data for patterns Review dynamic modeling of biochemical switches Who This Book Is For Life scientists with little or no programming experience, including undergraduate and graduate students, postdoctoral researchers in academia and industry, medical professionals, and teachers/lecturers. “A comprehensive introduction to using Python for computational biology... A lovely book with humor and perspective” -- John Novembre, Associate Professor of Human Genetics, University of Chicago and MacArthur Fellow “Fun, entertaining, witty and darn useful. A magical portal to the big data revolution” -- Sandro Santagata, Assistant Professor in Pathology, Harvard Medical School “Alex and Gordon’s enthusiasm for Python is contagious” -- Glenys Thomson Professor of Integrative Biology, University of California, Berkeley
Author: Rafael A. Irizarry
Publisher: CRC Press
ISBN: 1498775861
Category : Mathematics
Languages : en
Pages : 537
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Book Description
This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code that performs this analysis and connect the lines of code to the statistical and mathematical concepts explained.
Author: Kholmirzo Kholmurodov
Publisher: Nova Science Publishers
ISBN: 9781634825412
Category : Science
Languages : en
Pages : 0
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Book Description
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.
