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This list of protein subcellular localisation prediction tools includes software, databases, and web services that are used for protein subcellular localization prediction. Some tools are included that are commonly used to infer location through predicted structural properties, such as signal peptide or transmembrane helices , and these tools ...
Simple Modular Architecture Research Tool (SMART) is a biological database that is used in the identification and analysis of protein domains within protein sequences. [1] [2] SMART uses profile-hidden Markov models built from multiple sequence alignments to detect protein domains in protein sequences.
The development of protein domain databases such as Pfam (Protein Families Database) [10] allow us to find known domains within a query sequence, providing evidence for likely functions. The dcGO website [ 11 ] contains annotations to both the individual domains and supra-domains (i.e., combinations of two or more successive domains), thus via ...
PredictProtein (PP) is an automatic service that searches up-to-date public sequence databases, creates alignments, and predicts aspects of protein structure and function. Users send a protein sequence and receive a single file with results from database comparisons and prediction methods.
Constituent amino-acids can be analyzed to predict secondary, tertiary and quaternary protein structure. This list of protein structure prediction software summarizes notable used software tools in protein structure prediction, including homology modeling, protein threading, ab initio methods, secondary structure prediction, and transmembrane helix and signal peptide prediction.
InterPro functionally analyzes protein sequences and classifies them into protein families while predicting the presence of domains and functional sites. Contact; Research center: EMBL: Laboratory: European Bioinformatics Institute: Primary citation: The InterPro protein families and domains database: 20 years on [1] Release date: 1999: Access ...
The aim is to build tools that can accurately predict the outcome of protein targeting in cells. Prediction of protein subcellular localization is an important component of bioinformatics based prediction of protein function and genome annotation, and it can aid the identification of drug targets.
A step called domain parsing, or domain boundary prediction, is usually done first to split a protein into potential structural domains. As with the rest of tertiary structure prediction, this can be done comparatively from known structures [ 32 ] or ab initio with the sequence only (usually by machine learning , assisted by covariation). [ 33 ]