title: Web-based tools for protein classification.
abstract: Current proteomics technologies generate large number of data among which the investigator has to identify the promising diagnostic/prognostic biomarkers as well as potential therapeutic targets. For the latter, classification of proteins into meaningful families is needed. Current databases, featuring a high level of interconnectivity (cross referencing), provide the tools necessary to bring various data together, facilitating protein classification and elucidation of protein function and interoperativity. This chapter provides guidelines to explore the informationally rich peptide sequences generated by the application of the proteomics methodologies by the use of web-based tools, with the objective to predict potential protein function. After proper preprocessing (e.g., for internal repeats) of a query protein sequence, known domains can be identified, which aid in dividing the query into smaller meaningful parts. Any unclassified remainder of the protein provides the material for low-level comparative analysis for the discovery of distant homologues or candidate novel domain types to be verified experimentally.
authors.affiliation: Biomedical Research Foundation, Academy of Athens, Athens, Greece.
authors.forename: Costas D
authors.initials: CD
authors.lastname: Paliakasis
authors.forename: Ioannis
authors.initials: I
authors.lastname: Michalopoulos
authors.forename: Sophia
authors.initials: S
authors.lastname: Kossida
mesh_terms: D000595:Amino Acid Sequence; D030562:Databases, Protein; D006801:Humans; D020407:Internet; D008969:Molecular Sequence Data; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry / Q000145:classification* / Q000235:genetics; D020543:Proteome / Q000737:chemistry / Q000145:classification* / Q000235:genetics; D040901:Proteomics / Q000706:statistics & numerical data*; D012984:Software
chemical_list: D011506:Proteins; D020543:Proteome