Intrinsically Disordered Protein: Difference between revisions
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* [http://www.pondr.com/ PONDR] (Dunker Group, Indiana University and Molecular Kinetics, Inc., Indianapolis IN USA; Obradovic Group, Temple Univ., Philadelphia PA USA). "PONDR® functions from primary sequence data alone. The predictors are feedforward neural networks that use sequence information from windows of generally 21 amino acids. Attributes, such as the fractional composition of particular amino acids or hydropathy, are calculated over this window, and these values are used as inputs for the predictor. The neural network, which has been trained on a specific set of ordered and disordered sequences, then outputs a value for the central amino acid in the window. The predictions are then smoothed over a sliding window of 9 amino acids. If a residue value exceeds a threshold of 0.5 (the threshold used for training) the residue is considered disordered." (Quoted from the PONDR website.) | * [http://www.pondr.com/ PONDR] (Dunker Group, Indiana University and Molecular Kinetics, Inc., Indianapolis IN USA; Obradovic Group, Temple Univ., Philadelphia PA USA). "PONDR® functions from primary sequence data alone. The predictors are feedforward neural networks that use sequence information from windows of generally 21 amino acids. Attributes, such as the fractional composition of particular amino acids or hydropathy, are calculated over this window, and these values are used as inputs for the predictor. The neural network, which has been trained on a specific set of ordered and disordered sequences, then outputs a value for the central amino acid in the window. The predictions are then smoothed over a sliding window of 9 amino acids. If a residue value exceeds a threshold of 0.5 (the threshold used for training) the residue is considered disordered." (Quoted from the PONDR website.) | ||
* [https://app.strubi.ox.ac.uk/RONN/ RONN] (Esnouf Group, University of Oxford, UK). "We have developed the regional order neural network (RONN) software as an application of our recently developed ‘bio- basis function neural network’ pattern recognition algorithm to the detection of natively disordered regions in proteins. The results of blind-testing a panel of nine disorder prediction tools (including RONN) against 80 protein sequences derived from the Protein Data Bank shows that, based on the probability excess measure, RONN performed the best."<ref>PMID: 15947016</ref> | |||
* [http://prodata.swmed.edu/Lab/Software.htm WinDiso]<ref>PMID: 17893360</ref> (Grishin Lab, Dallas, Texas USA). "WinDiso is a linear, sequence- and alignment-based predictor of disordered/unfolded regions in proteins. It has the capability of adjusting for the increased tendency for disorder at protein termini. The simple weighted window-based algorithm and careful optimization technique make this a good predictor to use when trying to avoid bias toward special cases." (Quoted from the Grishin lab website.) | * [http://prodata.swmed.edu/Lab/Software.htm WinDiso]<ref>PMID: 17893360</ref> (Grishin Lab, Dallas, Texas USA). "WinDiso is a linear, sequence- and alignment-based predictor of disordered/unfolded regions in proteins. It has the capability of adjusting for the increased tendency for disorder at protein termini. The simple weighted window-based algorithm and careful optimization technique make this a good predictor to use when trying to avoid bias toward special cases." (Quoted from the Grishin lab website.) | ||