By Cathy H. Wu, Chuming Chen
With the fast improvement of proteomic applied sciences within the lifestyles sciences and in medical functions, many bioinformatics methodologies, databases, and software program instruments were built to aid comparative proteomics learn. In Bioinformatics for Comparative Proteomics, specialists within the box spotlight the present prestige, demanding situations, open difficulties, and destiny tendencies for constructing bioinformatics instruments and assets for comparative proteomics examine which will carry a definitive reference offering either the breadth and intensity wanted at the topic. dependent in 3 significant sections, this exact quantity covers simple bioinformatics frameworks in terms of comparative proteomics, bioinformatics databases and instruments for proteomics facts research, and built-in bioinformatics platforms and ways for learning comparative proteomics within the structures biology context. Written for the hugely winning tools in Molecular Biology™ sequence, the contributions during this e-book give you the meticulous, step by step description and implementation suggestion that's an important for buying optimum leads to the lab. entire and easy-to-use, Bioinformatics for Comparative Proteomics serves all readers who desire to know about cutting-edge bioinformatics databases and instruments, novel computational tools and destiny traits in proteomics info research, and comparative proteomics in structures biology.
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Extra resources for Bioinformatics for Comparative Proteomics
Unfortunately, this information seldom comes with the standard data files and formats and is usually not easily found in omics repositories unless a reanalysis is performed or the data is annotated by a curator. For example, tables of proteins present in a given proteomics experiment are routinely found as supplemental data in scientific publications, but are not available in a searchable or easily computable format. This is unfortunate as this supplemental information is the result of considerable analysis by the original authors of a study to minimize false positive and false negative results, thus often representing the “knowledge” that underlies additional analysis and conclusions reached in a publication.
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Bioinformatics for Comparative Proteomics by Cathy H. Wu, Chuming Chen