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This practical book teaches the skills that scientists need for turning large sequencing datasets into reproducible and robust biological findings. Many biologists begin their bioinformatics training by learning scripting languages like Python and R alongside the Unix command line. But there's a huge gap between knowing a few programming languages and being prepared to analyze large amounts of biological data. Rather than teach bioinformatics as a set of workflows that are likely to change with this rapidly evolving field, this book demsonstrates the practice of bioinformatics through data skills. Rigorous assessment of data quality and of the effectiveness of tools is the foundation of reproducible and robust bioinformatics analysis. Through open source and freely available tools, you'll learn not only how to do bioinformatics, but how to approach problems as a bioinformatician.Go from handling small problems with messy scripts to tackling large problems with clever methods and tools Focus on high-throughput (or "next generation") sequencing data Learn data analysis with modern methods, versus covering older theoretical concepts Understand how to choose and implement the best tool for the job Delve into methods that lead to easier, more reproducible, and robust bioinformatics analysis

An unprecedented wealth of data is being generated by genome sequencing projects and other experimental efforts to determine the structure and function of biological molecules. The demands and opportunities for interpreting these data are expanding more than ever. Biotechnology, pharmacology, and medicine will be particularly affected by the new results and the increased understanding of life at the molecular level. Bioinformatics is the development and application of computer methods for analysis, interpretation, and prediction, as well as for the design of experiments. It has emerged as a strategic frontier between biology and computer science. Machine learning approaches (e.g., neural networks, hidden Markov models, and belief networks) are ideally suited for areas where there is a lot of data but little theory—and this is exactly the situation in molecular biology. As with its predecessor, statistical model fitting, the goal in machine learning is to extract useful information from a body of data by building good probabilistic models. The particular twist behind machine learning, however, is to automate the process as much as possible. In this book, Pierre Baldi and Søren Brunak present the key machine learning approaches and apply them to the computational problems encountered in the analysis of biological data. The book is aimed at two types of researchers and students. First are the biologists and biochemists who need to understand new data-driven algorithms, such as neural networks and hidden Markov models, in the context of biological sequences and their molecular structure and function. Second are those with a primary background in physics, mathematics, statistics, or computer science who need to know more about specific applications in molecular biology.

Bioinformatics Algorithms: Design and Implementation in Python provides a comprehensive book on many of the most important bioinformatics problems, putting forward the best algorithms and showing how to implement them. The book focuses on the use of the Python programming language and its algorithms, which is quickly becoming the most popular language in the bioinformatics field. Readers will find the tools they need to improve their knowledge and skills with regard to algorithm development and implementation, and will also uncover prototypes of bioinformatics applications that demonstrate the main principles underlying real world applications.Presents an ideal text for bioinformatics students with little to no knowledge of computer programmingBased on over 12 years of pedagogical materials used by the authors in their own classroomsFeatures a companion website with downloadable codes and runnable examples (such as using Jupyter Notebooks) and exercises relating to the book

Bioinformatics is an interdisciplinary field of science, which combines biology, mathematics, computer science and statistics, for the development of methods and software tools to understand biological data. These may include the interpretation of the genetic basis of disease, unique adaptations, differences between populations, etc. It also aids in the understanding of the organizational principles between nucleic acids and protein sequences. Techniques such as image and signal processing facilitate the extraction of useful results from large amounts of data. Besides these, computational techniques of pattern recognition, visualization, data mining, etc. are used in bioinformatics. Research in this field explores the areas of drug design and discovery, gene finding, sequence alignment, prediction of gene expression and protein-protein interactions, among others. This book is a compilation of chapters that discuss the most vital concepts and emerging trends in the field of bioinformatics. The various advancements in this field are glanced at and their applications as well as ramifications are looked at in detail. This book is a vital tool for all researching and studying this field.

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Bioinformatics for Beginners: Genes, Genomes, Molecular Evolution, Databases and Analytical Tools provides a coherent and friendly treatment of bioinformatics for any student or scientist within biology who has not routinely performed bioinformatic analysis. The book discusses the relevant principles needed to understand the theoretical underpinnings of bioinformatic analysis and demonstrates, with examples, targeted analysis using freely available web-based software and publicly available databases. Eschewing non-essential information, the work focuses on principles and hands-on analysis, also pointing to further study options.Avoids non-essential coverage, yet fully describes the field for beginnersExplains the molecular basis of evolution to place bioinformatic analysis in biological contextProvides useful links to the vast resource of publicly available bioinformatic databases and analysis toolsContains over 100 figures that aid in concept discovery and illustration

Bioinformatics is an interdisciplinary field of science, which combines biology, mathematics, computer science and statistics, for the development of methods and software tools to understand biological data. These may include the interpretation of the genetic basis of disease, unique adaptations, differences between populations, etc. It also aids in the understanding of the organizational principles between nucleic acids and protein sequences. Techniques such as image and signal processing facilitate the extraction of useful results from large amounts of data. Besides these, computational techniques of pattern recognition, visualization, data mining, etc. are used in bioinformatics. Research in this field explores the areas of drug design and discovery, gene finding, sequence alignment, prediction of gene expression and protein-protein interactions, among others. This book is a compilation of chapters that discuss the most vital concepts and emerging trends in the field of bioinformatics. The various advancements in this field are glanced at and their applications as well as ramifications are looked at in detail. This book is a vital tool for all researching and studying this field.

Full four-color book. Some of the editors created the Bioconductor project and Robert Gentleman is one of the two originators of R. All methods are illustrated with publicly available data, and a major section of the book is devoted to fully worked case studies. Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.

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The computational education of biologists is changing to prepare students for facing the complex datasets of today's life science research. In this concise textbook, the authors' fresh pedagogical approaches lead biology students from first principles towards computational thinking. A team of renowned bioinformaticians take innovative routes to introduce computational ideas in the context of real biological problems. Intuitive explanations promote deep understanding, using little mathematical formalism. Self-contained chapters show how computational procedures are developed and applied to central topics in bioinformatics and genomics, such as the genetic basis of disease, genome evolution or the tree of life concept. Using bioinformatic resources requires a basic understanding of what bioinformatics is and what it can do. Rather than just presenting tools, the authors - each a leading scientist - engage the students' problem-solving skills, preparing them to meet the computational challenges of their life science careers.

Were you always curious about biology but were afraid to sit through long hours of dense reading? Did you like the subject when you were in high school but had other plans after you graduated? Now you can explore the human genome and analyze DNA without ever leaving your desktop! Bioinformatics For Dummies is packed with valuable information that introduces you to this exciting new discipline. This easy-to-follow guide leads you step by step through every bioinformatics task that can be done over the Internet. Forget long equations, computer-geek gibberish, and installing bulky programs that slow down your computer. You’ll be amazed at all the things you can accomplish just by logging on and following these trusty directions. You get the tools you need to: Analyze all types of sequences Use all types of databases Work with DNA and protein sequences Conduct similarity searches Build a multiple sequence alignment Edit and publish alignments Visualize protein 3-D structures Construct phylogenetic trees This up-to-date second edition includes newly created and popular databases and Internet programs as well as multiple new genomes. It provides tips for using servers and places to seek resources to find out about what’s going on in the bioinformatics world. Bioinformatics For Dummies will show you how to get the most out of your PC and the right Web tools so you’ll be searching databases and analyzing sequences like a pro!

This title is currently out of print. The third edition of Bioinformatics Algorithms has been released! This is Vol. 2 of Bioinformatics Algorithms: an Active Learning Approach, one of the first textbooks to emerge from the recent Massive Open Online Course (MOOC) revolution. A light-hearted and analogy-filled companion to the authors' acclaimed Bioinformatics Specialization on Coursera (http://coursera.org/specialization/bioinformatics/34), this book presents students with a dynamic approach to learning bioinformatics. It strikes a unique balance between practical challenges in modern biology and fundamental algorithmic ideas, thus capturing the interest of students of both biology and computer science. Each chapter begins with a biological question, such as "Are There Fragile Regions in the Human Genome?" or "Which DNA Patterns Play the Role of Molecular Clocks?" and then steadily develops the algorithmic sophistication required to answer this question. Hundreds of exercises are incorporated directly into the text as soon as they are needed; readers can test their knowledge through automated coding challenges on the Rosalind Bioinformatics Textbook Track (http://rosalind.info/problems/list-view/?location=bioinformatics-textbook-track).

The computational education of biologists is changing to prepare students for facing the complex datasets of today's life science research. In this concise textbook, the authors' fresh pedagogical approaches lead biology students from first principles towards computational thinking. A team of renowned bioinformaticians take innovative routes to introduce computational ideas in the context of real biological problems. Intuitive explanations promote deep understanding, using little mathematical formalism. Self-contained chapters show how computational procedures are developed and applied to central topics in bioinformatics and genomics, such as the genetic basis of disease, genome evolution or the tree of life concept. Using bioinformatic resources requires a basic understanding of what bioinformatics is and what it can do. Rather than just presenting tools, the authors - each a leading scientist - engage the students' problem-solving skills, preparing them to meet the computational challenges of their life science careers.

Bioinformatics: Principles and Applications is a comprehensive text designed to cater to the needs of undergraduate and postgraduate students of biotechnology and bioinformatics. This book will also cater to the requirements of students pursuing short-term diploma as also DOEACC courses in bioinformatics. Beginning with the aim and scope of bioinformatics, the book discusses in detail the essentials of the subject, such as bio-algorithms, bio-databases, molecular viewers, gene annotation methods, molecular phylogeny, and bio-molecular simulations. It further discusses the applications of bioinformatics in protein modeling and computer-aided drug design. The book also presents a discussion on molecular docking, including guidelines for using AutoDock software. The usage of select bioinformatics commercial software modules is also discussed. Written in a lucid style and user-friendly manner, the book with its wide and up to date coverage will be useful to students as well as practising professionals.

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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 applicationsLearn how to use Python modules for pattern matching, structured text processing, online data retrieval, and database accessDiscover generalized patterns that cover a large proportion of how Python code is used in bioinformaticsLearn how to apply the principles and techniques of object-oriented programmingBenefit from the "tips and traps" section in each chapter

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3rd edition. 540 pages. 11.00x8.75x1.00 inches. In Stock.