RaptorX Contact Prediction specifications


Unique identifier OMICS_09710
Name RaptorX Contact Prediction
Alternative name RaptorX-Contact
Interface Web user interface
Restrictions to use None
Input data Up to 50 protein sequences.
Input format FASTA
Computer skills Basic
Stability Stable
Maintained Yes


  • person_outline Jinbo Xu <>

Publications for RaptorX Contact Prediction

RaptorX Contact Prediction in publications

PMCID: 5938574
PMID: 29618526
DOI: 10.1098/rsif.2017.0387

[…] and pconsc []. however, blindly tested in the well-known casp competitions, these methods did not show any advantage over metapsicov []., recently, wang et al. [] proposed the deep learning method raptorx-contact, which significantly improves contact prediction over metapsicov and pure coevolution methods, especially for proteins without many sequence homologues. it employs a network […]

PMCID: 5868721
PMID: 29281821
DOI: 10.1016/j.celrep.2017.12.006

[…] resuspended in laemmli sample buffer, and analyzed by sds-page., transmembrane domain predictions were made with polyphobius () and topcons (); coiled coil predictions were made with coils (). raptorx-contact () was used to calculate contact maps from alignments of 584 tmco1 (188 residues), 453 emc3 (261 residues), 442 get1 (235 residues), and 485 wrb (174 residues) sequences […]

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RaptorX Contact Prediction institution(s)
Toyota Technological Institute, Chicago, IL, USA
RaptorX Contact Prediction funding source(s)
Supported by National Institutes of Health grant R01GM089753 and National Science Foundation grant DBI-1564955.

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