ProALIGN: Directly Learning Alignments for Protein Structure Prediction via Exploiting Context-Specific Alignment Motifs | Zendy

Lupeng Kong | Zendy; Fusong Ju | Zendy; WeiMou Zheng | Zendy; Jianwei Zhu | Zendy; Shiwei Sun | Zendy; Jinbo Xu | Zendy; Dongbo Bu | Zendy

Open Access

ProALIGN: Directly Learning Alignments for Protein Structure Prediction via Exploiting Context-Specific Alignment Motifs

Author(s) -

Lupeng Kong,

Fusong Ju,

WeiMou Zheng,

Jianwei Zhu,

Shiwei Sun,

Jinbo Xu,

Dongbo Bu

Publication year - 2022

Publication title -

journal of computational biology

Language(s) - Uncategorized

Resource type - Journals

SCImago Journal Rank - 0.585

H-Index - 95

eISSN - 1557-8666

pISSN - 1066-5277

DOI - 10.1089/cmb.2021.0430

Subject(s) - threading (protein sequence) , computer science , multiple sequence alignment , template , protein structure prediction , sequence alignment , structural alignment , artificial intelligence , convolutional neural network , pattern recognition (psychology) , artificial neural network , smith–waterman algorithm , protein structure , sequence (biology) , context (archaeology) , peptide sequence , biology , genetics , paleontology , biochemistry , gene , programming language

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research