HHalign-Kbest: exploring sub-optimal alignments for remote homology comparative modeling

@article{Yu2015HHalignKbestES,
  title={HHalign-Kbest: exploring sub-optimal alignments for remote homology comparative modeling},
  author={Jinchao Yu and G{\'e}raldine Picord and Pierre Tuff{\'e}ry and Rapha{\"e}l Gu{\'e}rois},
  journal={Bioinformatics},
  year={2015},
  volume={31 23},
  pages={3850-2}
}
MOTIVATION The HHsearch algorithm, implementing a hidden Markov model (HMM)-HMM alignment method, has shown excellent alignment performance in the so-called twilight zone (target-template sequence identity with ∼20%). However, an optimal alignment by HHsearch may contain small to large errors, leading to poor structure prediction if these errors are located in important structural elements. RESULTS HHalign-Kbest server runs a full pipeline, from the generation of suboptimal HMM-HMM alignments… CONTINUE READING
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