PconsC4: fast, free, easy, and accurate contact predictions
By Mirco Michel, David Ménendez Hurtado, Arne Elofsson. 2018
4 citations recorded by the source corpus.
Motivation Residue contact prediction was revolutionized recently by the introduction of direct coupling analysis (DCA). Further improvements, in particular for small families, have been obtained by the combination of DCA and deep learning methods. However, existing deep learning contact prediction methods often rely on a number of external programs and are therefore computationally expensive. Results Here, we introduce a novel contact predictor, PconsC4, which performs on par with state of the art methods. PconsC4 is heavily optimized, does not use any external programs and therefore is significantly faster and easier to use than other methods. Availability PconsC4 is freely available under the GPL license from https://github.com/ElofssonLab/PconsC4. Installation is easy using the pip command and works on any system with Python 3.5 or later and a modern GCC compiler. Contact arne@bioinfo.se
Subfields: Information Systems, Materials Chemistry, Molecular Biology
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Citations in the corpus
- DEEPCON: Protein Contact Prediction using Dilated Convolutional Neural Networks with Dropout (2019, methodology): “We also download the PconsC4 [2] tool available at https://github.”