Updated On September 11th, 2022
Looking for the best Bioinformatics Books? You aren't short of choices in 2022. The difficult bit is deciding the best Bioinformatics Books for you, but luckily that's where we can help. Based on testing out in the field with reviews, sells etc, we've created this ranked list of the finest Bioinformatics Books.
Rank | Product Name | Score | |
---|---|---|---|
1 |
![]() |
Bioinformatics Database Systems [Hardcover - Used]
Check Price
|
0%
|
2 |
![]() |
Ontologies for Bioinformatics [Hardcover - Used]
Check Price
|
0%
|
3 |
![]() |
Understanding Bioinformatics, Used [Paperback]
Check Price
|
0%
|
4 |
![]() |
Fundamental Concepts of Bioinformatics [Paperback - Used]
Check Price
|
0%
|
Our Score
CONDITION - USED - Pages can include limited notes and highlighting, and the copy can include "From the library of" labels or previous owner inscriptions. Accessories such as CD, codes, toys, may not be included. Modern biological databases comprise not only data, but also sophisticated query facilities and bioinformatics data analysis tools. This book provides an exploration through the world of Bioinformatics Database Systems . The book summarizes the popular and innovative bioinformatics repositories currently available, including popular primary genetic and protein sequence databases, phylogenetic databases, structure and pathway databases, microarray databases and boutique databases. It also explores the data quality and information integration issues currently involved with managing bioinformatics databases, including data quality issues that have been observed, and efforts in the data cleaning field. Biological data integration issues are also covered in-depth, and the book demonstrates how data integration can create new repositories to address the needs of the biological communities. It also presents typical data integration architectures employed in current bioinformatics databases. The latter part of the book covers biological data mining and biological data processing approaches using cloud-based technologies. General data mining approaches are discussed, as well as specific data mining methodologies that have been successfully deployed in biological data mining applications. Two biological data mining case studies are also included to illustrate how data, query, and analysis methods are integrated into user-friendly systems. Aimed at researchers and developers of bioinformatics database systems, the book is also useful as a supplementary textbook for a one-semester upper-level undergraduate course, or an introductory graduate bioinformatics course. About the Authors Kevin Byron is a PhD candidate in the Department of Computer Science at the New Jersey Institute of Technology. Katherine G. Herbert is Associate Professor of Computer Science at Montclair State University. Jason T.L. Wang is Professor of Bioinformatics and Computer Science at the New Jersey Institute of Technology.
Bioinformatics Database Systems [Hardcover - Used]
Our Score
CONDITION - USED - Pages can include limited notes and highlighting, and the copy can include "From the library of" labels or previous owner inscriptions. Accessories such as CD, codes, toys, may not be included. Ontologies as a critical framework for the vast amounts of data in the postgenomic era: an introduction to the basic concepts and applications of ontologies and ontology languages for the life sciences. Recent advances in biotechnology, spurred by the Human Genome Project, have resulted in the accumulation of vast amounts of new data. Ontologies--computer-readable, precise formulations of concepts (and the relationship among them) in a given field--are a critical framework for coping with the exponential growth of valuable biological data generated by high-output technologies. This book introduces the key concepts and applications of ontologies and ontology languages in bioinformatics and will be an essential guide for bioinformaticists, computer scientists, and life science researchers.The three parts of Ontologies for Bioinformatics ask, and answer, three pivotal questions: what ontologies are; how ontologies are used; and what ontologies could be (which focuses on how ontologies could be used for reasoning with uncertainty). The authors first introduce the notion of an ontology, from hierarchically organized ontologies to more general network organizations, and survey the best-known ontologies in biology and medicine. They show how to construct and use ontologies, classifying uses into three categories: querying, viewing, and transforming data to serve diverse purposes. Contrasting deductive, or Boolean, logic with inductive reasoning, they describe the goal of a synthesis that supports both styles of reasoning. They discuss Bayesian networks as a way of expressing uncertainty, describe data fusion, and propose that the World Wide Web can be extended to support reasoning with uncertainty. They call this inductive reasoning web the Bayesian web.
Ontologies for Bioinformatics, Used [Hardcover]
Our Score
Suitable for advanced undergraduates and postgraduates, Understanding Bioinformatics provides a definitive guide to this vibrant and evolving discipline. The book takes a conceptual approach. It guides the reader from first principles through to an understanding of the computational techniques and the key algorithms. Understanding Bioinformatics is an invaluable companion for students from their first encounter with the subject through to more advanced studies. The book is divided into seven parts, with the opening part introducing the basics of nucleic acids, proteins and databases. Subsequent parts are divided into 'Applications' and 'Theory' Chapters, allowing readers to focus their attention effectively. In each section, the Applications Chapter provides a fast and straightforward route to understanding the main concepts and 'getting started'. Each of these is then followed by Theory Chapters which give greater detail and present the underlying mathematics. In Part 2, Sequence Alignments, the Applications Chapter shows the reader how to get started on producing and analyzing sequence alignments, and using sequences for database searching, while the next two chapters look closely at the more advanced techniques and the mathematical algorithms involved. Part 3 covers evolutionary processes and shows how bioinformatics can be used to help build phylogenetic trees. Part 4 looks at the characteristics of whole genomes. In Parts 5 and 6 the focus turns to secondary and tertiary structure - predicting structural conformation and analysing structure-function relationships. The last part surveys methods of analyzing data from a set of genes or proteins of an organism and is rounded off with an overview of systems biology. The writing style of Understanding Bioinformatics is notable for its clarity, while the extensive, full-color artwork has been designed to present the key concepts with simplicity and consistency. Each chapter uses mind-maps and flow diagrams to give an overview of the conceptual links within each topic.
Understanding Bioinformatics, Used [Paperback]
Our Score
CONDITION - USED - Pages can include limited notes and highlighting, and the copy can include "From the library of" labels or previous owner inscriptions. Accessories such as CD, codes, toys, may not be included. "Fundamental Concepts of Bioinformatics" is the first book co-authored by a biologist and computer scientist that is specifically designed to make bioinformatics accessible and provide readers for more advanced work. Readers learn what programs are available for analyzing data, how to understand the basic algorithms that underlie these programs, what bioinformatic research is like, and other basic concepts. Information flows easily from one topic to the next, with enough detail to support the major concepts without overwhelming readers. Problems at the end of each chapter use real data to help readers apply what they have learned so they know how to critically evaluate results from both a statistical and biological point of view.
Fundamental Concepts of Bioinformatics, Used [Paperback]