Exploring Bioinformatics: A Project-Based Approach Is Intended For An Introductory Course In Bioinformatics At The Undergraduate Level. Through Hands-On Projects, Students Are Introduced To Current Biological Problems And Then Explore And Develop Bioinformatic Solutions To These Issues. Each Chapter Presents A Key Problem, Provides Basic Biological Concepts, Introduces Computational Techniques To Address The Problem, And Guides Students Through The Use Of Existing Web-Based Tools And Existing Software Solutions. This Progression Prepares Students To Tackle The On-Your-Own Project, Where They Develop Their Own Software Solutions. Topics Such As Antibiotic Resistance, Genetic Disease, And Genome Sequencing Provide Context And Relevance To Capture Student Interest.

Thoroughly revised and updated, Exploring Bioinformatics: A Project-Based Approach, Second Edition is intended for an introductory course in bioinformatics at the undergraduate level. Through hands-on projects, students are introduced to current biological problems and then explore and develop bioinformatic solutions to these issues. Each chapter presents a key problem, provides basic biological concepts, introduces computational techniques to address the problem, and guides students through the use of existing web-based tools and software solutions. This progression prepares students to tackle the On-Your-Own Project, where they develop their own software solutions. Topics such as antibiotic resistance, genetic disease, and genome sequencing provide context and relevance to capture student interest.

Exploring Bioinformatics is a concise yet comprehensive textbook of bioinformatics that provides a broad introduction to the entire field. Written specifically for a life science audience, the basics of bioinformatics are explained, followed by discussions of the state-of-the-art computational tools available to solve biological research problems. All key areas of bioinformatics are covered including biological databases, sequence alignment, gene and promoter prediction, molecular phylogenetics, structural bioinformatics, genomics, and proteomics. The book emphasizes how computational methods work and compares the strengths and weaknesses of different methods. This balanced yet easily accessible text will be invaluable to students who do not have sophisticated computational backgrounds. Technical details of computational algorithms are explained with a minimum use of mathematical formulas; graphical illustrations are used in their place to aid understanding. The effective synthesis of existing literature as well as in-depth and up-to-date coverage of all key topics in bioinformatics make this an ideal textbook for all bioinformatics courses taken by life science students and for researchers wishing to develop their knowledge of bioinformatics to facilitate their own research.

This textbook introduces fundamental concepts of bioinformatics and computational biology to the students and researchers in biology, medicine, veterinary science, agriculture, and bioengineering . The respective chapters provide detailed information on biological databases, sequence alignment, molecular evolution, next-generation sequencing, systems biology, and statistical computing using R. The book also presents a case-based discussion on clinical, veterinary, agricultural bioinformatics, and computational bioengineering for application-based learning in the respective fields. Further, it offers readers guidance on reconstructing and analysing biological networks and highlights computational methods used in systems medicine and genome-wide association mapping of diseases. Given its scope, this textbook offers an essential introductory book on bioinformatics and computational biology for undergraduate and graduate students in the life sciences, botany, zoology, physiology, biotechnology, bioinformatics, and genomic science as well as systems biology, bioengineering and the agricultural, and veterinary sciences.

Bioinformatics Algorithms: an Active Learning Approach is one of the first textbooks to emerge from the recent Massive Online Open Course (MOOC) revolution. A light-hearted and analogy-filled companion to the authors' acclaimed online course (http://coursera.org/course/bioinformatics), 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 biology and computer science students alike.Each chapter begins with a central 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 Rosalind (http://rosalind.info), an online platform for learning bioinformatics.The textbook website (http://bioinformaticsalgorithms.org) directs readers toward additional educational materials, including video lectures and PowerPoint slides.

Rapid advances in high-throughput genome sequencing technologies foreshadow a near-future in which millions of individuals will gain affordable access to their complete genome sequence. This promises to give unprecedented insights into the fundamental biological nature of ourselves and our species: where we came from, how we are born, how we interact with our environment, how we get sick, how we get well, and how we age. Personal genomics is therefore an important component of the inevitable transition towards personalized medicine, as the medical establishment begins to explore and evaluate the role of personal genomics in health and medicine. However there is currently very little training available for medical practitioners. Exploring Personal Genomics provides a novel, inquiry-based approach to understanding and interpreting the practical, medical, and societal aspects of personal genomic information. It is presented in two parts: the first provides readers of all backgrounds with a fundamental understanding of the biology of human genomes, information on how to obtain and understand digital representations of personal genomic data, tools and techniques for exploring the personal genomics of ancestry and genealogy, discovery and interpretation of genetic trait associations, and the role of personal genomics in drug response. The second part offers more advanced readers an understanding of the science, tools, and techniques for investigating interactions between a personal genome and the environment, connecting DNA to physiology, assessing rare variants and structural variation, and exploring resources for performing personal biological investigation. This advanced textbook is primarily aimed at undergraduate and graduate students taking classes in genomic medicine, genetics, and bioinformatics. It will also be of relevance and use to medical practitioners, evolutionary biologists, geneticists and individuals interested in exploring their personal genetic data.

These interactive tutorials are used in conjunction with the online tutorials found at www.whfreeman.com/young, to guide students through live searches and analyses on the National Center for Biotechnology Information (NCBI) database. This edition includes three new tutorials on the COGs database, functional analysis, and environmental genomics.

Over the last decade biological research has changed completely. The reductionism approach of studying only a few biological entities at a time in the past is being replaced by the study of the biological system as a whole today. This requires that existing biological knowledge (data) is made readily available. Effective integration of biological knowledge from databases scattered around the internet and other information resources (for example experimental data) is recognized as a pre-requisite for many aspects of biological research. Systems for the integration of biological knowledge have to overcome several challenges: biological data sources may contain similar or overlapping coverage and the user of such systems is faced with the challenge of generating a consensus data set or selecting the "best" data source; different access methods to databases, different data formats, different naming conventions and erroneous or missing data. To address these challenges and enable effective integration of biological knowledge, the ONDEX system was created. ONDEX provides an integrated view across biological data sources to the user. Here the basic principles behind ONDEX are presented.

This text features detailed descriptions of methods of bio molecular sequence and structure analyses of interest to students and practitioners of bioinformatics both in the corporate and academic sectors.