Edited by
Zoé Lacroix, Arizona State University, USA
Terence Critchlow, Lawrence Livermore National Laboratory, Livermore, CA, USA
Description
Life science data integration and interoperability is one of the most challenging problems facing bioinformatics today. In the current
age of the life sciences, investigators have to interpret many types of information from a variety of sources: lab instruments, public
databases, gene expression profiles, raw sequence traces, single nucleotide polymorphisms, chemical screening data, proteomic data, putative
metabolic pathway models, and many others. Unfortunately, scientists are not currently able to easily identify and access this information
because of the variety of semantics, interfaces, and data formats used by the underlying data sources.
Bioinformatics: Managing
Scientific Data tackles this challenge head-on by discussing the current approaches and variety of systems available to help bioinformaticians
with this increasingly complex issue. The heart of the book lies in the collaboration efforts of eight distinct bioinformatics teams
that describe their own unique approaches to data integration and interoperability. Each system receives its own chapter where the lead
contributors provide precious insight into the specific problems being addressed by the system, why the particular architecture was chosen,
and details on the system's strengths and weaknesses. In closing, the editors provide important criteria for evaluating these systems
that bioinformatics professionals will find valuable.
Audience:
Bioinformaticians involved in data management (development, design, management, etc) at corporations and research companies. CS and life science students in bioinformatics programs.
