Porter, PaleAle 4.0: high-accuracy prediction of protein secondary structure and relative solvent accessibility

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Porter, PaleAle 4.0: high-accuracy prediction of protein secondary structure and relative solvent accessibility

SUMMARY Protein secondary structure and solvent accessibility predictions are a fundamental intermediate step towards protein structure and function prediction. We present new systems for the ab initio prediction of protein secondary structure and solvent accessibility, Porter 4.0 and PaleAle 4.0. Porter 4.0 predicts secondary structure correctly for 82.2% of residues. PaleAle 4.0's accuracy is...

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Protein domains are considered the basic unit of protein tertiary structure. We have developed a 1D-Recursive Neural Network (1D-RNN) called DOMpro that predicts protein domains using a combination of evolutionary information in the form of profiles and predicted secondary structure and relative solvent accessibility. DOMpro is trained and tested on a curated dataset derived from the CATH datab...

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

UNLABELLED 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...

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ژورنال

عنوان ژورنال: Bioinformatics

سال: 2013

ISSN: 1367-4803,1460-2059

DOI: 10.1093/bioinformatics/btt344