Zobrazeno 1 - 10
of 654
pro vyhledávání: '"protein secondary structure prediction"'
Publikováno v:
Biomolecular Concepts, Vol 15, Iss 1, Pp 399-411 (2024)
Computational biology faces many challenges like protein secondary structure prediction (PSS), prediction of solvent accessibility, etc. In this work, we addressed PSS prediction. PSS is based on sequence-structure mapping and interaction among amino
Externí odkaz:
https://doaj.org/article/bee5e0f1f2934cc6892cb2774c2259a7
Autor:
Vrushali Bongirwar, A. S. Mokhade
Publikováno v:
IEEE Access, Vol 12, Pp 115346-115355 (2024)
Protein secondary structure prediction plays a pivotal role in deciphering protein function and structure, with implications for drug discovery, functional annotation, and molecular biology research. Deep learning techniques, particularly recurrent n
Externí odkaz:
https://doaj.org/article/144116bcd89541dcb3090db44480d4e7
Publikováno v:
Mathematical Biosciences and Engineering, Vol 20, Iss 2, Pp 2203-2218 (2023)
As an important task in bioinformatics, protein secondary structure prediction (PSSP) is not only beneficial to protein function research and tertiary structure prediction, but also to promote the design and development of new drugs. However, current
Externí odkaz:
https://doaj.org/article/5f25209f3e42461e980f4bc8dc1116e1
Publikováno v:
Molecules, Vol 28, Iss 20, p 7046 (2023)
Protein structure prediction represents a significant challenge in the field of bioinformatics, with the prediction of protein structures using backbone dihedral angles recently achieving significant progress due to the rise of deep neural network re
Externí odkaz:
https://doaj.org/article/916096f831164eb6932fbfbc076979b6
Publikováno v:
BMC Bioinformatics, Vol 23, Iss 1, Pp 1-16 (2022)
Abstract Background The prediction of protein secondary structures is a crucial and significant step for ab initio tertiary structure prediction which delivers the information about proteins activity and functions. As the experimental methods are exp
Externí odkaz:
https://doaj.org/article/b7928a31b15a42be8b44f1f25fd1c79c
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 20, Iss , Pp 6271-6286 (2022)
This paper aims to provide a comprehensive review of the trends and challenges of deep neural networks for protein secondary structure prediction (PSSP). In recent years, deep neural networks have become the primary method for protein secondary struc
Externí odkaz:
https://doaj.org/article/13f52e29f0074cb4b968f0b7aec5c767
Publikováno v:
IEEE Access, Vol 10, Pp 117469-117476 (2022)
As a basic feature extraction method, convolutional neural networks have some information loss problems when dealing with sequence problems, and a temporal convolutional network can compensate for this problem. Howerover, ordinary temporal convolutio
Externí odkaz:
https://doaj.org/article/74a82ae1c68e49b28ad4caff9e76e4ff
Publikováno v:
IEEE Access, Vol 10, Pp 27759-27770 (2022)
Trying to extract features from complex sequential data for classification and prediction problems is an extremely difficult task. This task is even more challenging when both the upstream and downstream information of a time-series is important to p
Externí odkaz:
https://doaj.org/article/709439a7518a4deb895ed7f79b4128d2
Publikováno v:
Frontiers in Bioengineering and Biotechnology, Vol 11 (2023)
Protein secondary structure prediction (PSSP) is a challenging task in computational biology. However, existing models with deep architectures are not sufficient and comprehensive for deep long-range feature extraction of long sequences. This paper p
Externí odkaz:
https://doaj.org/article/e627c655b8b94c2ba49702a5a576cec1
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