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.

* Provides a clear overview of the state-of-the-art in data integration and interoperability in genomics, highlighting a variety of systems and giving insight into the strengths and weaknesses of their different approaches.
* Discusses shared vocabulary, design issues, complexity of use cases, and the difficulties of transferring existing data management approaches to bioinformatics systems, which serves to connect computer and life scientists.
* Written by the primary contributors of eight reputable bioinformatics systems in academia and industry including: BioKris, TAMBIS, K2, GeneExpress, P/FDM, MBM, SDSC, SRS, and DiscoveryLink.

The advances in genomic technologies, such as microarrays and high throughput sequencing,
have expanded the realm of possibilities for capturing data and analyzing it using automated
computer driven bioinformatics tools. With the completion of the sequencing of genomes of
human and several model organisms, a quest for scientific discoveries being fueled by
integrative and multidimensional techniques in mathematics and computational sciences. In
this volume, leading researchers and experts have provided an overview of significant
concepts from biological, mathematical, and computational perspectives. It provides a high level view of fungal genomic data integration and annotation, classification of proteins and identification of vaccine targets, identification of secretome or secreted proteins in fungal genomes, as well as tools for analyzing microarray expression
profiles.

* Provides a survey of theoretical underpinnings on the technological tools and applications
* Discusses the tools utilized for the annotation of fungal genomes and addresses issues related to automated annotation generation in a high throughput biotechnology environment
* describing the applications of the concepts and methodologies presented throughout the book