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PSI-blast based secondary structure PREDiction (PSIPRED) is a method used to investigate protein structure. It uses artificial neural network machine learning methods in its algorithm. [ 2 ] [ 3 ] [ 4 ] It is a server-side program, featuring a website serving as a front-end interface, which can predict a protein's secondary structure ( beta ...
Predicts secondary structure and solvent accessibility: Webserver: server and API: 1998 PredictProtein: Profile-based neural network: Webserver: server: 1992 PSIPRED: two feed-forward neural networks which perform an analysis on output obtained from PSI-BLAST: Webserver: server: 1999
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.
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 ...
This is a server that aggregates several structure prediction methods. It includes the newly implemented method also known as PSIPRED (Predict Secondary Protein Structure), a technique for protein secondary structure prediction, and the other techniques Predict Transmembrane Topology (MEMSAT3), and Fold Recognition (GenTHREADER).
Prediction of transmembrane helices in protein. PSIPRED 2.45: Secondary structure prediction. PSIPRED achieves an average Q3 score of 80.6% for secondary structure prediction. PS_scan: Tool for local PROSITE scans. VADAR 1.4: Locally developed protein structure analysis tool. BASys uses VADAR to analyze protein structures for secondary ...
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.
The protein structure prediction remains an extremely difficult and unresolved undertaking. The two main problems are the calculation of protein free energy and finding the global minimum of this energy. A protein structure prediction method must explore the space of possible protein structures which is astronomically large.