Dataset Information

DIRECT: RNA contact predictions by integrating structural patterns.

ABSTRACT: BACKGROUND:It is widely believed that tertiary nucleotide-nucleotide interactions are essential in determining RNA structure and function. Currently, direct coupling analysis (DCA) infers nucleotide contacts in a sequence from its homologous sequence alignment across different species. DCA and similar approaches that use sequence information alone typically yield a low accuracy, especially when the available homologous sequences are limited. Therefore, new methods for RNA structural contact inference are desirable because even a single correctly predicted tertiary contact can potentially make the difference between a correct and incorrectly predicted structure. Here we present a new method DIRECT (Direct Information REweighted by Contact Templates) that incorporates a Restricted Boltzmann Machine (RBM) to augment the information on sequence co-variations with structural features in contact inference. RESULTS:Benchmark tests demonstrate that DIRECT achieves better overall performance than DCA approaches. Compared to mfDCA and plmDCA, DIRECT produces a substantial increase of 41 and 18%, respectively, in accuracy on average for contact prediction. DIRECT improves predictions for long-range contacts and captures more tertiary structural features. CONCLUSIONS:We developed a hybrid approach that incorporates a Restricted Boltzmann Machine (RBM) to augment the information on sequence co-variations with structural templates in contact inference. Our results demonstrate that DIRECT is able to improve the RNA contact prediction.

SUBMITTER: Jian Y

PROVIDER: S-EPMC6794908 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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DIRECT: RNA contact predictions by integrating structural patterns.

Jian Yiren Y Wang Xiaonan X Qiu Jaidi J Wang Huiwen H Liu Zhichao Z Zhao Yunjie Y Zeng Chen C

BMC bioinformatics 20191015 1

<h4>Background</h4>It is widely believed that tertiary nucleotide-nucleotide interactions are essential in determining RNA structure and function. Currently, direct coupling analysis (DCA) infers nucleotide contacts in a sequence from its homologous sequence alignment across different species. DCA and similar approaches that use sequence information alone typically yield a low accuracy, especially when the available homologous sequences are limited. Therefore, new methods for RNA structural cont ...[more]

PMID: 31615418

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Dataset Information

DIRECT: RNA contact predictions by integrating structural patterns.

Publications

DIRECT: RNA contact predictions by integrating structural patterns.

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