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Porter: a new, accurate server for protein secondary structure prediction

Authors:

Gianluca Pollastri,

Aoife MclysaghtAuthors Info & Claims

Bioinformatics, Volume 21, Issue 8

Pages 1719 - 1720

https://doi.org/10.1093/bioinformatics/bti203

Published: 15 April 2005 Publication History

Abstract

Summary: Porter is a new system for protein secondary structure prediction in three classes. Porter relies on bidirectional recurrent neural networks with shortcut connections, accurate coding of input profiles obtained from multiple sequence alignments, second stage filtering by recurrent neural networks, incorporation of long range information and large-scale ensembles of predictors. Porter's accuracy, tested by rigorous 5-fold cross-validation on a large set of proteins, exceeds 79%, significantly above a copy of the state-of-the-art SSpro server, better than any system published to date.

Availability: Porter is available as a public web server at http://distill.ucd.ie/porter/

Contact: [email protected]

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Mohanty RManoswini MDhal AGanguly N(2022) In silico analysis of a novel protein in CAR T- cell therapy for the treatment of hematologic cancer through molecular modelling, docking, and dynamics approachComputers in Biology and Medicine10.1016/j.compbiomed.2022.106285151:PAOnline publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1016/j.compbiomed.2022.106285
Wardah WKhan MSharma ARashid M(2019)Protein secondary structure prediction using neural networks and deep learningComputational Biology and Chemistry10.1016/j.compbiolchem.2019.10709381:C(1-8)Online publication date: 1-Aug-2019
https://dl.acm.org/doi/10.1016/j.compbiolchem.2019.107093
Al Nasr KYousef FJones CJebril RHaspel NCowen LShehu AKahveci TPozzi G(2017)Geometry Analysis for Protein Secondary Structures Matching ProblemProceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics10.1145/3107411.3107505(716-721)Online publication date: 20-Aug-2017
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Published In

Bioinformatics Volume 21, Issue 8

April 2005

456 pages

ISSN:1367-4803

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Oxford University Press, Inc.

United States

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Published: 15 April 2005

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Mohanty RManoswini MDhal AGanguly N(2022) In silico analysis of a novel protein in CAR T- cell therapy for the treatment of hematologic cancer through molecular modelling, docking, and dynamics approachComputers in Biology and Medicine10.1016/j.compbiomed.2022.106285151:PAOnline publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1016/j.compbiomed.2022.106285
Wardah WKhan MSharma ARashid M(2019)Protein secondary structure prediction using neural networks and deep learningComputational Biology and Chemistry10.1016/j.compbiolchem.2019.10709381:C(1-8)Online publication date: 1-Aug-2019
https://dl.acm.org/doi/10.1016/j.compbiolchem.2019.107093
Al Nasr KYousef FJones CJebril RHaspel NCowen LShehu AKahveci TPozzi G(2017)Geometry Analysis for Protein Secondary Structures Matching ProblemProceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics10.1145/3107411.3107505(716-721)Online publication date: 20-Aug-2017
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Handl JGarza-Fabre MKandathil SLovell S(2017)On heuristic bias in fragment-assembly methods for protein structure predictionProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3067695.3082545(1652-1656)Online publication date: 15-Jul-2017
https://dl.acm.org/doi/10.1145/3067695.3082545
Biswas ARanjan DZubair MZeil SNasr KHe J(2017)An Effective Computational Method Incorporating Multiple Secondary Structure Predictions in Topology Determination for Cryo-EM ImagesIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2016.254372114:3(578-586)Online publication date: 1-May-2017
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Spencer MEickholt JCheng J(2015)A deep learning network approach to ab initio protein secondary structure predictionIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2014.234396012:1(103-112)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.1109/TCBB.2014.2343960
Al Nasr KRanjan DZubair MChen LHe J(2014)Solving the secondary structure matching problem in cryo-EM de novo modeling using a constrained K-shortest path graph algorithmIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2014.230280311:2(419-430)Online publication date: 1-Mar-2014
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Yang WWang KZuo W(2013)Prediction of protein secondary structure using large margin nearest neighbour classificationInternational Journal of Bioinformatics Research and Applications10.1504/IJBRA.2013.0524459:2(207-219)Online publication date: 1-Mar-2013
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Nasr KChen LRanjan DZubair MSi DHe J(2013)A Constrained K-shortest Path Algorithm to Rank the Topologies of the Protein Secondary Structure Elements Detected in CryoEM Volume MapsProceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics10.1145/2506583.2506705(749-755)Online publication date: 22-Sep-2013
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Al Nasr KLiu CRwebangira MBurge LHe J(2013)Intensity-Based Skeletonization of CryoEM Gray-Scale Images Using a True Segmentation-Free AlgorithmIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2013.12110:5(1289-1298)Online publication date: 1-Sep-2013
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