FALCON : A high-throughput protein structure prediction server based on remote homologue recognition
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 462-464 |
Journal / Publication | Bioinformatics |
Volume | 32 |
Issue number | 3 |
Online published | 10 Oct 2015 |
Publication status | Published - 1 Feb 2016 |
Link(s)
Abstract
Summary: The protein structure prediction approaches can be categorized into template-based modeling (including homology modeling and threading) and free modeling. However, the existing threading tools perform poorly on remote homologous proteins. Thus, improving fold recognition for remote homologous proteins remains a challenge. Besides, the proteome-wide structure prediction poses another challenge of increasing prediction throughput. In this study, we presented FALCON
Citation Format(s)
FALCON: A high-throughput protein structure prediction server based on remote homologue recognition. / Wang, Chao; Zhang, Haicang; Zheng, Wei-Mou et al.
In: Bioinformatics, Vol. 32, No. 3, 01.02.2016, p. 462-464.
In: Bioinformatics, Vol. 32, No. 3, 01.02.2016, p. 462-464.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review