By Simon J. Hubbard, Andrew R. Jones
The box of proteomics strikes swiftly, as new tools, ideas, functions, criteria, types and software program seem virtually every day. In Proteome Bioinformatics, professional researchers discover this ever-changing box, delivering the reader with a mixture of evaluation and method chapters which deal with the basics of research tools, algorithms, info criteria and databases. Chapters contain sensible issues for interpreting database seek effects, annotating genomes, dashing up searches, and responding to express information processing demanding situations. As a quantity of the hugely profitable equipment in Molecular Biology sequence, this paintings presents the type of specified description and implementation recommendation that's an important for purchasing optimum results.
Comprehensive and ground-breaking, Proteome Bioinformatics is a necessary guidebook for the beginner and professional alike, protecting themes that deal with quite a lot of info research and administration problems.
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Additional info for Proteome Bioinformatics
Sample text
Selection of Database Search Parameters Very poor results can be obtained from high quality data if users do not take care to select search parameters appropriately. Even the smallest mis-setting of a parameter can reduce the number of confident identifications to a small fraction of those that are possible. Some of the key parameters are outlined subsequently. Mass type. Although most modern mass spectrometers have sufficient resolution to be able to routinely determine mono isotopic peptide and fragment m/z values from spectra, large molecules and older instruments may not always lead to such good resolution.
Park, C. , Klammer, A. , MacCoss, M. , and Noble, W. S. (2008) Rapid and accurate peptide identification from tandem mass spectra. Journal of Proteome Research 7, 3022–27. 15. Shilov, I. , Seymour, S. , Patel, A. , Tang, W. , Keating, S. , Hunter, C. , Nuwaysir, L. , and Schaeffer, D. A. (2007) The paragon algorithm, a next generation search engine that uses sequence temperature values and feature probabilities to identify peptides from tandem mass spectra. Molecular & Cellular Proteomics 6, 1638–55.
And MacCoss, M. J. (2008) A fast SEQUEST cross correlation algorithm. Journal of Proteome Research 7, 4598–602. 8. Eng, J. , McCormack, A. , and Yates, J. R. (1994) An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. Journal of the American Society for Mass Spectrometry 5, 976–89. 40 Hubbard 9. Perkins, D. , Pappin, D. J. , Creasy, D. , and Cottrell, J. S. (1999) Probabilitybased protein identification by searching sequence databases using mass spectrometry data.