1. A First Course In Computers 2003 Edition (With Cd)
This book offers an in depth study of computer concepts and step by step procedure in explaining the MS Office package. A separate section is devoted to E mails and introduction to web design.
2. Foundations of Computing (English, Paperback, Sinhs Pradeep K.)
3. Introduction to Bioinformatics
An Introduction to Bioinformatics introduces students to the immense power of bioinformatics as a set of scientific tools. The book explains how to access the data archives of genomes and proteins, and the kinds of questions these data and tools can answer, such as how to make inferences from data archives and how to make connections among them to derive useful and interesting predictions.
Blending factual content with many opportunities for active learning, An Introduction to Bioinformatics offers a truly reader-friendly way to get to grips with this subject, making it the ideal resource for anyone new to the field.
4. Bioinformatics: Methods and Applications: Genomics, Proteomics and Drug Discovery by S. C. Rastogi
5. Bioinformatics: Concepts, Skills & Applications
6. Principles of Genome Analysis and Genomics
With the first draft of the human genome project in the public domain and full analyses of model genomes now available, the subject matter of ‘Principles of Genome Analysis and Genomics’ is even ‘hotter’ now than when the first two editions were published in 1995 and 1998. In the new edition of this very practical guide to the different techniques and theory behind genomes and genome analysis, Sandy Primrose and new author Richard Twyman provide a fresh look at this topic. In the light of recent exciting advancements in the field, the authors have completely revised and rewritten many parts of the new edition with the addition of five new chapters. Aimed at upper level students, it is essential that in this extremely fast moving topic area the text is up to date and relevant.
- Completely revised new edition of an established textbook.
- Features new chapters and examples from exciting new research in genomics, including the human genome project.
- Excellent new co-author in Richard Twyman, also co-author of the new edition of hugely popular Principles of Gene Manipulation.
7. Bioinformatics: A Practical Handbook of Next Generation Sequencing and Its Applications
Rapid technological developments have led to increasingly efficient sequencing approaches. Next Generation Sequencing (NGS) is increasingly common and has become cost-effective, generating an explosion of sequenced data that need to be analyzed. The skills required to apply computational analysis to target research on a wide range of applications that include identifying causes of cancer, vaccine design, new antibiotics, drug development, personalized medicine and higher crop yields in agriculture are highly sought after.
This invaluable book provides step-by-step guides to complex topics that make it easy for readers to perform essential analyses from raw sequenced data to answering important biological questions. It is an excellent hands-on material for teachers who conduct courses in bioinformatics and as a reference material for professionals. The chapters are written to be standalone recipes making it suitable for readers who wish to self-learn selected topics. Readers will gain skills necessary to work on sequenced data from NGS platforms and hence making themselves more attractive to employers who need skilled bioinformaticians to handle the deluge of data.
Readership: It is a necessary companion for undergraduates, graduate students, researchers and anyone interested in the exponentially growing field of bioinformatics.
8. Bioinformatics with R Cookbook
This book is an easy-to-follow, stepwise guide to handle real life Bioinformatics problems. Each recipe comes with a detailed explanation to the solution steps. A systematic approach, coupled with lots of illustrations, tips, and tricks will help you as a reader grasp even the trickiest of concepts without difficulty.This book is ideal for computational biologists and bioinformaticians with basic knowledge of R programming, bioinformatics and statistics. If you want to understand various critical concepts needed to develop your computational models in Bioinformatics, then this book is for you. Basic knowledge of R is expected.
9. Bioinformatics with Python Cookbook
Learn how to use modern Python bioinformatics libraries and applications to do cutting-edge research in computational biology
About This Book
- Discover and learn the most important Python libraries and applications to do a complex bioinformatics analysis
- Focuses on the most modern tools to do research with next generation sequencing, genomics, population genetics, phylogenomics, and proteomics
- Uses real-world examples and teaches you to implement high-impact research methods
Who This Book Is For
If you have intermediate-level knowledge of Python and are well aware of the main research and vocabulary in your bioinformatics topic of interest, this book will help you develop your knowledge further.
What You Will Learn
- Gain a deep understanding of Python’s fundamental bioinformatics libraries and be exposed to the most important data science tools in Python
- Process genome-wide data with Biopython
- Analyze and perform quality control on next-generation sequencing datasets using libraries such as PyVCF or PySAM
- Use DendroPy and Biopython for phylogenetic analysis
- Perform population genetics analysis on large datasets
- Simulate complex demographies and genomic features with simuPOP
If you are either a computational biologist or a Python programmer, you will probably relate to the expression “explosive growth, exciting times”. Python is arguably the main programming language for big data, and the deluge of data in biology, mostly from genomics and proteomics, makes bioinformatics one of the most exciting fields in data science.
Using the hands-on recipes in this book, you’ll be able to do practical research and analysis in computational biology with Python. We cover modern, next-generation sequencing libraries and explore real-world examples on how to handle real data. The main focus of the book is the practical application of bioinformatics, but we also cover modern programming techniques and frameworks to deal with the ever increasing deluge of bioinformatics data.
10. Bioinformatics Data Skills: Reproducible and Robust Research with Open Source Tools
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
11. Building Bioinformatics Solutions: with Perl, R and MySQL
Modern bioinformatics encompasses a broad and ever-changing range of activities involved with the management and analysis of data from molecular biology experiments. Despite the diversity of activities and applications, the basic methodology and core tools needed to tackle bioinformatics problems is common to many projects. Building Bioinformatics Solutions provides a comprehensive introduction to this methodology, explaining how to acquire and use the most popular development tools, how to apply them to build processing pipelines, and how to make the results available through visualizations and web-based services for deployment either locally or via the Internet.
The main development tools covered in this book are the MySQL database management system, the Perl programming language, and the R language for statistical computing. These industry standard open source tools form the core of many bioinformatics projects, both in academia and industry. The methodologies introduced are platform independent, and all the examples that feature have been tested on Windows, Linux and Mac OS.
This advanced textbook is suitable for graduate students and researchers in the life sciences who wish to automate analyses or create their own databases and web-based tools. No prior knowledge of software development is assumed.
Having worked through the book, the reader should have the necessary core skills to develop computational solutions for their specific research programmes. The book will also help the reader overcome the inertia associated with penetrating this field, and provide them with the confidence and understanding required to go on to develop more advanced bioinformatics skills.
12. Beginning Perl for Bioinformatics
With its highly developed capacity to detect patterns in data, Perl has become one of the most popular languages for biological data analysis. But if you’re a biologist with little or no programming experience, starting out in Perl can be a challenge. Many biologists have a difficult time learning how to apply the language to bioinformatics. The most popular Perl programming books are often too theoretical and too focused on computer science for a non-programming biologist who needs to solve very specific problems.Beginning Perl for Bioinformatics is designed to get you quickly over the Perl language barrier by approaching programming as an important new laboratory skill, revealing Perl programs and techniques that are immediately useful in the lab. Each chapter focuses on solving a particular bioinformatics problem or class of problems, starting with the simplest and increasing in complexity as the book progresses. Each chapter includes programming exercises and teaches bioinformatics by showing and modifying programs that deal with various kinds of practical biological problems. By the end of the book you’ll have a solid understanding of Perl basics, a collection of programs for such tasks as parsing BLAST and GenBank, and the skills to take on more advanced bioinformatics programming. Some of the later chapters focus in greater detail on specific bioinformatics topics. This book is suitable for use as a classroom textbook, for self-study, and as a reference.The book covers:
- Programming basics and working with DNA sequences and strings
- Debugging your code
- Simulating gene mutations using random number generators
- Regular expressions and finding motifs in data
- Arrays, hashes, and relational databases
- Regular expressions and restriction maps
- Using Perl to parse PDB records, annotations in GenBank, and BLAST output
13. BIOINFORMATICS ALGORITHMS,VOL.II
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.
14. XML for Bioinformatics
Introduction The goal of this book is to introduce XML to a bioinformatics audience. It does so by introducing the fundamentals of XML, Document Type De?nitions (DTDs), XML Namespaces, XML Schema, and XML parsing, and illustrating these concepts with speci?c bioinformatics case studies. The book does not assume any previous knowledge of XML and is geared toward those who want a solid introduction to fundamental XML concepts. The book is divided into nine chapters: Chapter 1: Introduction to XML for Bioinformatics. This chapter provides an introduction to XML and describes the use of XML in biological data exchange. A bird’s-eye view of our ?rst case study, the Distributed Annotation System (DAS), is provided and we examine a sample DAS XML document. The chapter concludes with a discussion of the pros and cons of using XML in bioinformatic applications. Chapter 2: Fundamentals of XML and BSML. This chapter introduces the fundamental concepts of XML and the Bioinformatic Sequence Markup Language (BSML). We explore the origins of XML, de?ne basic rules for XML document structure, and introduce XML Na- spaces. We also explore several sample BSML documents and visualize these documents in the TM Rescentris Genomic Workspace Viewer.
15. Bioinformatics For Dummies
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!