Bioinformatics: Managing Scientific Data (The Morgan Kaufmann Series in Multimedia Information and Systems)
Life science data integration and interoperability is one of the most challenging problems facing bioinformatics today. Get and download textbook Bioinformatics: Managing Scientific Data (The Morgan Kaufmann Series in Multimedia Information and Systems) for free
Next generation sequencing is revolutionizing molecular biology. Owing to this new technology it is now possible to carry out a panoply of experiments at an unprecedented low cost and high speed. These go from sequencing whole genomes, transcriptomes and small non-coding RNAs to description of methylated regions, identification protein – DNA interaction sites and detection of structural variation. The generation of gigabases of sequence information for each of this huge bandwidth of applications in just a few days makes the development of bioinformatics applications for next generation sequencing data analysis as urgent as challenging.
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 Bioinformatics new edition
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Bioinformatics Textbook
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
Bioinformatics: Managing Scientific Data tackles this challenge head-on by discussing the
