rMSA: A Sequence Search and Alignment Algorithm to Improve RNA Structure Modeling-Reference-Cited by-同舟云学术

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

Published:2022-12 Issue: Volume: Page:167904
ISSN:0022-2836
Container-title:Journal of Molecular Biology
language:en
Short-container-title:Journal of Molecular Biology

Author:

Zhang Chengxin,Zhang Yang,Pyle Anna Marie

Funder

National Science Foundation

Howard Hughes Medical Institute

National Human Genome Research Institute

National Institute of General Medical Sciences

National Institute of Allergy and Infectious Diseases

Publisher

Elsevier BV

Subject

Molecular Biology,Structural Biology

Reference43 articles.

1. DeepMSA: constructing deep multiple sequence alignment to improve contact prediction and fold-recognition for distant-homology proteins;Zhang;Bioinformatics,2020

2. Protein structure determination using metagenome sequence data;Ovchinnikov;Science,2017

3. Fueling ab initio folding with marine metagenomics enables structure and function predictions of new protein families;Wang;Genome Biol.,2019

4. RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning;Singh;Nat. Commun.,2019

5. Single-sequence and profile-based prediction of RNA solvent accessibility using dilated convolutional neural network;Hanumanthappa;Bioinformatics,2020

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