Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Yaoguang Xing"'
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-17 (2024)
Abstract Significant research progress has been made in the field of protein structure and fitness prediction. Particularly, single-sequence-based structure prediction methods like ESMFold and OmegaFold achieve a balance between inference speed and p
Externí odkaz:
https://doaj.org/article/bcabb9eb2633459f8fcee7b9503715ff
Publikováno v:
BMC Bioinformatics, Vol 21, Iss 1, Pp 1-12 (2020)
Abstract Background Despite the great advance of protein structure prediction, accurate prediction of the structures of mainly β proteins is still highly challenging, but could be assisted by the knowledge of residue-residue pairing in β strands. P
Externí odkaz:
https://doaj.org/article/f31f9f862d7745a996acf0b35db3413a
Publikováno v:
BMC Bioinformatics, Vol 21, Iss 1, Pp 1-12 (2020)
Background Despite the great advance of protein structure prediction, accurate prediction of the structures of mainly β proteins is still highly challenging, but could be assisted by the knowledge of residue-residue pairing in β strands. Previously
Publikováno v:
Nature Machine Intelligence. 2:25-33
Predicting the structures of proteins from amino acid sequences is of great importance. Recently, the accuracy of de novo protein structure prediction has been substantially improved when assisted by information about the contact between residues, wh
Additional file 1 of RDb2C2: an improved method to identify the residue-residue pairing in β strands
Additional file 1: Table S1. List of mainly β proteins collected from the CASP11–13 datasets.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7e78aa896c009f2c2fe9fd068e59732f
Publikováno v:
BMC Bioinformatics
Background Despite the great advance of protein structure prediction, accurate prediction of the structures of mainly β proteins is still highly challenging, but could be assisted by the knowledge of residue-residue pairing in β strands. Previously
Publikováno v:
Natural Language Processing and Chinese Computing ISBN: 9783030322359
NLPCC (2)
NLPCC (2)
Sentiment analysis models based on neural network architecture have achieved promising results. Some works bring improvement to these neural models via taking user and product into account. However, the way of utilizing significant role user and prod
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3be371d0f7c42dc132b683fe812ce95f
https://doi.org/10.1007/978-3-030-32236-6_33
https://doi.org/10.1007/978-3-030-32236-6_33