Download or read book Managing Your Biological Data with Python written by Allegra Via and published by CRC Press. This book was released on 2014-03-18 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take Control of Your Data and Use Python with ConfidenceRequiring no prior programming experience, Managing Your Biological Data with Python empowers biologists and other life scientists to work with biological data on their own using the Python language. The book teaches them not only how to program but also how to manage their data. It shows how

Download or read book Managing Your Biological Data with Python written by Allegra Via and published by CRC Press. This book was released on 2014-03-18 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take Control of Your Data and Use Python with Confidence Requiring no prior programming experience, Managing Your Biological Data with Python empowers biologists and other life scientists to work with biological data on their own using the Python language. The book teaches them not only how to program but also how to manage their data. It shows how to read data from files in different formats, analyze and manipulate the data, and write the results to a file or computer screen. The first part of the text introduces the Python language and teaches readers how to write their first programs. The second part presents the basic elements of the language, enabling readers to write small programs independently. The third part explains how to create bigger programs using techniques to write well-organized, efficient, and error-free code. The fourth part on data visualization shows how to plot data and draw a figure for an article or slide presentation. The fifth part covers the Biopython programming library for reading and writing several biological file formats, querying the NCBI online databases, and retrieving biological records from the web. The last part provides a cookbook of 20 specific programming "recipes," ranging from secondary structure prediction and multiple sequence alignment analyses to superimposing protein three-dimensional structures. Tailoring the programming topics to the everyday needs of biologists, the book helps them easily analyze data and ultimately make better discoveries. Every piece of code in the text is aimed at solving real biological problems.

Download or read book Big Data in Omics and Imaging written by Momiao Xiong and published by CRC Press. This book was released on 2017-12-01 with total page 668 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data in Omics and Imaging: Association Analysis addresses the recent development of association analysis and machine learning for both population and family genomic data in sequencing era. It is unique in that it presents both hypothesis testing and a data mining approach to holistically dissecting the genetic structure of complex traits and to designing efficient strategies for precision medicine. The general frameworks for association analysis and machine learning, developed in the text, can be applied to genomic, epigenomic and imaging data. FEATURES Bridges the gap between the traditional statistical methods and computational tools for small genetic and epigenetic data analysis and the modern advanced statistical methods for big data Provides tools for high dimensional data reduction Discusses searching algorithms for model and variable selection including randomization algorithms, Proximal methods and matrix subset selection Provides real-world examples and case studies Will have an accompanying website with R code The book is designed for graduate students and researchers in genomics, bioinformatics, and data science. It represents the paradigm shift of genetic studies of complex diseases– from shallow to deep genomic analysis, from low-dimensional to high dimensional, multivariate to functional data analysis with next-generation sequencing (NGS) data, and from homogeneous populations to heterogeneous population and pedigree data analysis. Topics covered are: advanced matrix theory, convex optimization algorithms, generalized low rank models, functional data analysis techniques, deep learning principle and machine learning methods for modern association, interaction, pathway and network analysis of rare and common variants, biomarker identification, disease risk and drug response prediction.

Download or read book Big Data Analysis for Bioinformatics and Biomedical Discoveries written by Shui Qing Ye and published by CRC Press. This book was released on 2016-01-13 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Demystifies Biomedical and Biological Big Data AnalysesBig Data Analysis for Bioinformatics and Biomedical Discoveries provides a practical guide to the nuts and bolts of Big Data, enabling you to quickly and effectively harness the power of Big Data to make groundbreaking biological discoveries, carry out translational medical research, and implem

Download or read book RNA seq Data Analysis written by Eija Korpelainen and published by CRC Press. This book was released on 2014-09-19 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: The State of the Art in Transcriptome AnalysisRNA sequencing (RNA-seq) data offers unprecedented information about the transcriptome, but harnessing this information with bioinformatics tools is typically a bottleneck. RNA-seq Data Analysis: A Practical Approach enables researchers to examine differential expression at gene, exon, and transcript le

Download or read book Stochastic Dynamics for Systems Biology written by Christian Mazza and published by CRC Press. This book was released on 2016-04-19 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is one of the first books to provide a systematic study of the many stochastic models used in systems biology. The book shows how the mathematical models are used as technical tools for simulating biological processes and how the models lead to conceptual insights on the functioning of the cellular processing system. Examples cover the phage lambda genetic switch, eukaryotic gene expression, noise propagation in gene networks, and more. Most of the text should be accessible to scientists with basic knowledge in calculus and probability theory.

Download or read book Chromatin written by Ralf Blossey and published by CRC Press. This book was released on 2017-08-04 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: An invaluable resource for computational biologists and researchers from other fields seeking an introduction to the topic, Chromatin: Structure, Dynamics, Regulation offers comprehensive coverage of this dynamic interdisciplinary field, from the basics to the latest research. Computational methods from statistical physics and bioinformatics are detailed whenever possible without lengthy recourse to specialized techniques.

Download or read book Computational Exome and Genome Analysis written by Peter N. Robinson and published by CRC Press. This book was released on 2017-09-13 with total page 575 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exome and genome sequencing are revolutionizing medical research and diagnostics, but the computational analysis of the data has become an extremely heterogeneous and often challenging area of bioinformatics. Computational Exome and Genome Analysis provides a practical introduction to all of the major areas in the field, enabling readers to develop a comprehensive understanding of the sequencing process and the entire computational analysis pipeline.

Download or read book Mathematical Models of Plant Herbivore Interactions written by Zhilan Feng and published by CRC Press. This book was released on 2017-09-07 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Models of Plant-Herbivore Interactions addresses mathematical models in the study of practical questions in ecology, particularly factors that affect herbivory, including plant defense, herbivore natural enemies, and adaptive herbivory, as well as the effects of these on plant community dynamics. The result of extensive research on the use of mathematical modeling to investigate the effects of plant defenses on plant-herbivore dynamics, this book describes a toxin-determined functional response model (TDFRM) that helps explains field observations of these interactions. This book is intended for graduate students and researchers interested in mathematical biology and ecology.

Download or read book Statistical Modeling and Machine Learning for Molecular Biology written by Alan Moses and published by CRC Press. This book was released on 2017-01-06 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: • Assumes no background in statistics or computers • Covers most major types of molecular biological data • Covers the statistical and machine learning concepts of most practical utility (P-values, clustering, regression, regularization and classification) • Intended for graduate students beginning careers in molecular biology, systems biology, bioengineering and genetics

Download or read book An Introduction to Physical Oncology written by Vittorio Cristini and published by CRC Press. This book was released on 2017-06-26 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Physical oncology has the potential to revolutionize cancer research and treatment. The fundamental rationale behind this approach is that physical processes, such as transport mechanisms for drug molecules within tissue and forces exchanged by cancer cells with tissue, may play an equally important role as biological processes in influencing progression and treatment outcome. This book introduces the emerging field of physical oncology to a general audience, with a focus on recent breakthroughs that help in the design and discovery of more effective cancer treatments. It describes how novel mathematical models of physical transport processes incorporate patient tissue and imaging data routinely produced in the clinic to predict the efficacy of many cancer treatment approaches, including chemotherapy and radiation therapy. By helping to identify which therapies would be most beneficial for an individual patient, and quantifying their effects prior to actual implementation in the clinic, physical oncology allows doctors to design treatment regimens customized to each patient’s clinical needs, significantly altering the current clinical approach to cancer treatment and improving the outcomes for patients.

Download or read book Bioinformatics Programming Using Python written by Mitchell L Model and published by "O'Reilly Media, Inc.". This book was released on 2009-12-08 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: Powerful, flexible, and easy to use, Python is an ideal language for building software tools and applications for life science research and development. This unique book shows you how to program with Python, using code examples taken directly from bioinformatics. In a short time, you'll be using sophisticated techniques and Python modules that are particularly effective for bioinformatics programming. Bioinformatics Programming Using Python is perfect for anyone involved with bioinformatics -- researchers, support staff, students, and software developers interested in writing bioinformatics applications. You'll find it useful whether you already use Python, write code in another language, or have no programming experience at all. It's an excellent self-instruction tool, as well as a handy reference when facing the challenges of real-life programming tasks. Become familiar with Python's fundamentals, including ways to develop simple applications Learn how to use Python modules for pattern matching, structured text processing, online data retrieval, and database access Discover generalized patterns that cover a large proportion of how Python code is used in bioinformatics Learn how to apply the principles and techniques of object-oriented programming Benefit from the "tips and traps" section in each chapter

Download or read book Bayesian Phylogenetics written by Ming-Hui Chen and published by CRC Press. This book was released on 2014-05-27 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering a rich diversity of models, Bayesian phylogenetics allows evolutionary biologists, systematists, ecologists, and epidemiologists to obtain answers to very detailed phylogenetic questions. Suitable for graduate-level researchers in statistics and biology, Bayesian Phylogenetics: Methods, Algorithms, and Applications presents a snapshot of current trends in Bayesian phylogenetic research. Encouraging interdisciplinary research, this book introduces state-of-the-art phylogenetics to the Bayesian statistical community and, likewise, presents state-of-the-art Bayesian statistics to the phylogenetics community. The book emphasizes model selection, reflecting recent interest in accurately estimating marginal likelihoods. It also discusses new approaches to improve mixing in Bayesian phylogenetic analyses in which the tree topology varies. In addition, the book covers divergence time estimation, biologically realistic models, and the burgeoning interface between phylogenetics and population genetics.

Download or read book Computational and Visualization Techniques for Structural Bioinformatics Using Chimera written by Forbes J. Burkowski and published by CRC Press. This book was released on 2014-07-29 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Step-by-Step Guide to Describing Biomolecular StructureComputational and Visualization Techniques for Structural Bioinformatics Using Chimera shows how to perform computations with Python scripts in the Chimera environment. It focuses on the three core areas needed to study structural bioinformatics: biochemistry, mathematics, and computation.Und

Download or read book Introduction to Proteins written by Amit Kessel and published by CRC Press. This book was released on 2018-03-22 with total page 1423 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Proteins provides a comprehensive and state-of-the-art introduction to the structure, function, and motion of proteins for students, faculty, and researchers at all levels. The book covers proteins and enzymes across a wide range of contexts and applications, including medical disorders, drugs, toxins, chemical warfare, and animal behavior. Each chapter includes a Summary, Exercies, and References. New features in the thoroughly-updated second edition include: A brand-new chapter on enzymatic catalysis, describing enzyme biochemistry, classification, kinetics, thermodynamics, mechanisms, and applications in medicine and other industries. These are accompanied by multiple animations of biochemical reactions and mechanisms, accessible via embedded QR codes (which can be viewed by smartphones) An in-depth discussion of G-protein-coupled receptors (GPCRs) A wider-scale description of biochemical and biophysical methods for studying proteins, including fully accessible internet-based resources, such as databases and algorithms Animations of protein dynamics and conformational changes, accessible via embedded QR codes Additional features Extensive discussion of the energetics of protein folding, stability and interactions A comprehensive view of membrane proteins, with emphasis on structure-function relationship Coverage of intrinsically unstructured proteins, providing a complete, realistic view of the proteome and its underlying functions Exploration of industrial applications of protein engineering and rational drug design Each chapter includes a Summary, Exercies, and References Approximately 300 color images Downloadable solutions manual available at www.crcpress.com For more information, including all presentations, tables, animations, and exercises, as well as a complete teaching course on proteins' structure and function, please visit the author's website: http://ibis.tau.ac.il/wiki/nir_bental/index.php/Introduction_to_Proteins_Book. Praise for the first edition "This book captures, in a very accessible way, a growing body of literature on the structure, function and motion of proteins. This is a superb publication that would be very useful to undergraduates, graduate students, postdoctoral researchers, and instructors involved in structural biology or biophysics courses or in research on protein structure-function relationships." --David Sheehan, ChemBioChem, 2011 "Introduction to Proteins is an excellent, state-of-the-art choice for students, faculty, or researchers needing a monograph on protein structure. This is an immensely informative, thoroughly researched, up-to-date text, with broad coverage and remarkable depth. Introduction to Proteins would provide an excellent basis for an upper-level or graduate course on protein structure, and a valuable addition to the libraries of professionals interested in this centrally important field." --Eric Martz, Biochemistry and Molecular Biology Education, 2012

Download or read book Introduction to Mathematical Oncology written by Yang Kuang and published by CRC Press. This book was released on 2018-09-03 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Mathematical Oncology presents biologically well-motivated and mathematically tractable models that facilitate both a deep understanding of cancer biology and better cancer treatment designs. It covers the medical and biological background of the diseases, modeling issues, and existing methods and their limitations. The authors introduce mathematical and programming tools, along with analytical and numerical studies of the models. They also develop new mathematical tools and look to future improvements on dynamical models. After introducing the general theory of medicine and exploring how mathematics can be essential in its understanding, the text describes well-known, practical, and insightful mathematical models of avascular tumor growth and mathematically tractable treatment models based on ordinary differential equations. It continues the topic of avascular tumor growth in the context of partial differential equation models by incorporating the spatial structure and physiological structure, such as cell size. The book then focuses on the recent active multi-scale modeling efforts on prostate cancer growth and treatment dynamics. It also examines more mechanistically formulated models, including cell quota-based population growth models, with applications to real tumors and validation using clinical data. The remainder of the text presents abundant additional historical, biological, and medical background materials for advanced and specific treatment modeling efforts. Extensively classroom-tested in undergraduate and graduate courses, this self-contained book allows instructors to emphasize specific topics relevant to clinical cancer biology and treatment. It can be used in a variety of ways, including a single-semester undergraduate course, a more ambitious graduate course, or a full-year sequence on mathematical oncology.

Download or read book Bioinformatics Data Skills written by Vince Buffalo and published by "O'Reilly Media, Inc.". This book was released on 2015-07 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn the data skills necessary for turning large sequencing datasets into reproducible and robust biological findings. With this practical guide, youâ??ll learn how to use freely available open source tools to extract meaning from large complex biological data sets. At no other point in human history has our ability to understand lifeâ??s complexities been so dependent on our skills to work with and analyze data. This intermediate-level book teaches the general computational and data skills you need to analyze biological data. If you have experience with a scripting language like Python, youâ??re ready to get started. Go from handling small problems with messy scripts to tackling large problems with clever methods and tools Process bioinformatics data with powerful Unix pipelines and data tools Learn how to use exploratory data analysis techniques in the R language Use efficient methods to work with genomic range data and range operations Work with common genomics data file formats like FASTA, FASTQ, SAM, and BAM Manage your bioinformatics project with the Git version control system Tackle tedious data processing tasks with with Bash scripts and Makefiles