Improved protein contact predictions with the MetaPSICOV2 server in CASP12

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Buchan, Daniel W.A and Jones, David T. 2018. Improved protein contact predictions with the MetaPSICOV2 server in CASP12. Proteins, 86(S1), pp. 78-83. ISSN 0887-3585 [Article]

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Official URL: https://onlinelibrary.wiley.com/doi/full/10.1002/p...

Abstract or Description

In this paper, we present the results for the MetaPSICOV2 contact prediction server in the CASP12 community experiment (http://predictioncenter.org). Over the 35 assessed Free Modelling target domains the MetaPSICOV2 server achieved a mean precision of 43.27%, a substantial increase relative to the server's performance in the CASP11 experiment. In the following paper, we discuss improvements to the MetaPSICOV2 server, covering both changes to the neural network and attempts to integrate contact predictions on a domain basis into the prediction pipeline. We also discuss some limitations in the CASP12 assessment which may have overestimated the performance of our method.

Item Type:

Article

Identification Number (DOI):

https://doi.org/10.1002/prot.25379

Additional Information:

Funding Information: Biotechnology and Biological Sciences Research Council. Grant Number: BB/M011712/1

Keywords:

contact prediction, machine learning, meta‐prediction, bioinformatics

Departments, Centres and Research Units:

Computing

Dates: