Work

rMSA: A Sequence Search and Alignment Algorithm to Improve RNA Structure Modeling

Year: 2022

Type: article

Abstract: The multiple sequence alignment (MSA) is the entry point of many RNA structure modeling tasks, such as prediction of RNA secondary structure (rSS) and contacts. However, there are few automated programs for generating high quality MSAs of target RNA molecules. We have developed rMSA, a hierarchical pipeline for sensitive search and accurate alignment of RNA homologs for a target RNA. On a diverse set of 365 non-redundant RNA structures, rMSA significantly outperforms an existing MSA generation method (RNAcmap) by approximately 20% and 5% higher F1-scores for rSS and long-range contact prediction, respectively. rMSA is available at https://zhanggroup.org/rMSA/ and https://github.com/pylelab/rMSA.

Source: Journal of Molecular Biology

DOI: 10.1016/j.jmb.2022.167904

Authors: Chengxin Zhang, Yang Zhang, Anna Marie Pyle

Institutions: Howard Hughes Medical Institute, University of Michigan, Yale University

Language: English

Topic: RNA and protein synthesis mechanisms

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: hybrid

Estimated APC paid: $3,750