By Tamariz N.
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This selection of state-of-the-art methodologies for learning membrane transporters and channels takes good thing about the entire most up-to-date advancements in biomedical learn, together with pharmacogenomcs, bioinformatics, and microarray applied sciences. The authors clarify databases and instruments for bioinformatics reviews, offer sensible directions for microarray experiments and knowledge research, and illustrate using small attitude X-ray scattering, nuclear magnetic resonance (NMR), and molecular modeling to review the structural biology of membrane transporters.
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There can be valuable knowledge buried in various unorganized data and the process of data integration can help “unveil” the hidden knowledge. In this chapter, we will briefly introduce methodologies on how to extract useful information from various data so that the information can be applied directly in research and development projects. We will also describe the organization of membrane transporter data, such as how to understand terminologies and the classification of membrane transporters. Various bioinformatics approaches have been used in transporter studies.
Jr. (2000) A functional–phylogenetic classification system for transmembrane solute transporters. Microbiol. Mol. Biol. Rev. 64, 354–411. 4. Saier, M. , Jr. (2000) Vectorial metabolism and the evolution of transport systems. J. Bacteriol. 182, 5029–5035. 5. Saier, M. , Jr. (2001) Evolution of transport proteins, in Genetic Engineering. Principles and Methods, Vol. 23 (J. K. ), Kluwer Academic/Plenum, New York, pp. 1–10. 6. Busch, W. and Saier, M. , Jr. (2002) The Transporter Classification (TC) System, 2002, Crit.
3. INPUT AND OUTPUT The input of searching can be a protein sequence. Users can choose the database they want to search against and other flavors and views to format their search results. Figure 5 shows a sample searching result using a TAP1 protein sequence. For example, Protein kinase C (PKC) phosphorylation sites and their positions are shown. 3. 1. WHEN TO USE Detecting transmembrane regions can be especially useful in membrane transporters. 56 56 Yan Fig. 5. Motif analysis of the TAP gene using ProfileScan.