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Paircoil2: Improved Prediction
of Coiled Coils from Sequence
Andrew V. McDonnell, Taijiao Jiang, Amy E. Keating & Bonnie Berger
Abstract
We introduce Paircoil2,
a new version of the Paircoil program, which uses pairwise residue probabilities
to detect coiled-coil motifs in protein sequence data. Paircoil2 achieves
98% sensitivity and 97% specificity on known coiled coils in leave-family-out
cross-validation. It also shows superior performance compared with published
methods in tests on proteins of known structure. Paircoil2 is freely available
as a web application and for download at http://paircoil2.csail.mit.edu.
References:
[1] Andrew V. McDonnell, Taijiao Jiang, Amy E. Keating & Bonnie Berger.
Paircoil2: Improved Prediction of Coiled Coils from Sequence. Bioinformatics
22(3) 356-358, 2006. |
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