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Porter 5: fast, state-of-the-art ab initio prediction of protein secondary structure in 3 and 8 classes

View ORCID ProfileMirko Torrisi, View ORCID ProfileManaz Kaleel, View ORCID ProfileGianluca Pollastri
doi: https://doi.org/10.1101/289033
Mirko Torrisi
University College Dublin
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Manaz Kaleel
University College Dublin
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Gianluca Pollastri
University College Dublin
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Abstract

Motivation Although secondary structure predictors have been developed for decades, current ab initio methods have still some way to go to reach their theoretical limits. Moreover, the continuous effort towards harnessing ever expanding data sets and more sophisticated, deeper Ma-chine Learning techniques, has not come to an end.

Results Here we present Porter 5, the latest release of one of the best performing ab initio secondary structure predictors. Version 5 achieves 84% accuracy (84% SOV) when tested on 3 classes, and 73% accuracy (77% SOV) on 8 classes, on a large independent set, significantly outper-forming all the most recent ab initio predictors we have tested.

Availability The web and standalone versions of Porter5 are available at http://distilldeep.ucd.ie/porter/.

Contact gianluca.pollastri{at}ucd.ie

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted October 05, 2018.
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Porter 5: fast, state-of-the-art ab initio prediction of protein secondary structure in 3 and 8 classes
Mirko Torrisi, Manaz Kaleel, Gianluca Pollastri
bioRxiv 289033; doi: https://doi.org/10.1101/289033
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Porter 5: fast, state-of-the-art ab initio prediction of protein secondary structure in 3 and 8 classes
Mirko Torrisi, Manaz Kaleel, Gianluca Pollastri
bioRxiv 289033; doi: https://doi.org/10.1101/289033

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