Results 21 to 30 of about 986,500 (268)

ISSEC: inferring contacts among protein secondary structure elements using deep object detection

open access: yesBMC Bioinformatics, 2020
Background The formation of contacts among protein secondary structure elements (SSEs) is an important step in protein folding as it determines topology of protein tertiary structure; hence, inferring inter-SSE contacts is crucial to protein structure ...
Qi Zhang   +6 more
doaj   +1 more source

The hydration of protein secondary structures

open access: yesFEBS Letters, 1987
The hydration of the main‐chain carbonyl (CO) groups in proteins have been studied using infra‐red spectroscopy, and computer‐graphics analysis of high resolution protein crystal structures. The IR measurements indicate that the strength of water binding to the CO groups is lower in β‐sheet proteins compared with α‐helical ones. Analysis of the protein
Barlow, D.J., Poole, P.L.
openaire   +2 more sources

Prediction of protein secondary structure based on an improved channel attention and multiscale convolution module

open access: yesFrontiers in Bioengineering and Biotechnology, 2022
Prediction of the protein secondary structure is a key issue in protein science. Protein secondary structure prediction (PSSP) aims to construct a function that can map the amino acid sequence into the secondary structure so that the protein secondary ...
Xin Jin   +9 more
doaj   +1 more source

3-State Protein Secondary Structure Prediction based on SCOPe Classes

open access: yesBrazilian Archives of Biology and Technology, 2021
Improving the accuracy of protein secondary structure prediction has been an important task in bioinformatics since it is not only the starting point in obtaining tertiary structure in hierarchical modeling but also enhances sequence analysis and ...
Sema Atasever   +3 more
doaj   +1 more source

Extended secondary structures in proteins

open access: yesBiochimica et Biophysica Acta (BBA) - Proteins and Proteomics, 2014
Super secondary structures of proteins have been systematically searched and classified, but not enough attention has been devoted to such large edifices beyond the basic identification of secondary structures. The objective of the present study is to show that the association of secondary structures that share some of their backbone residues is a ...
Degrève, Léo   +2 more
openaire   +2 more sources

PCI-SS: MISO dynamic nonlinear protein secondary structure prediction

open access: yesBMC Bioinformatics, 2009
Background Since the function of a protein is largely dictated by its three dimensional configuration, determining a protein's structure is of fundamental importance to biology.
Aboul-Magd Mohammed O   +2 more
doaj   +1 more source

PS4: a next-generation dataset for protein single-sequence secondary structure prediction

open access: yesBioTechniques, 2023
Protein secondary structure prediction is a subproblem of protein folding. A light-weight algorithm capable of accurately predicting secondary structure from only the protein residue sequence could provide useful input for tertiary structure prediction ...
Omar Peracha
doaj   +1 more source

Convolution-Bidirectional Temporal Convolutional Network for Protein Secondary Structure Prediction

open access: yesIEEE Access, 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.
Yunqing Zhang, Yuming Ma, Yihui Liu
doaj   +1 more source

Extracting Physicochemical Features to Predict Protein Secondary Structure

open access: yesThe Scientific World Journal, 2013
We propose a protein secondary structure prediction method based on position-specific scoring matrix (PSSM) profiles and four physicochemical features including conformation parameters, net charges, hydrophobic, and side chain mass.
Yin-Fu Huang, Shu-Ying Chen
doaj   +1 more source

Combining Deep Neural Networks for Protein Secondary Structure Prediction

open access: yesIEEE Access, 2020
By combining convolutional neural networks (CNN) and long short term memory networks (LSTM) into the learning structure, this paper presents a supervised learning method called combining deep neural networks (CDNN) for protein secondary structure ...
Shusen Zhou   +4 more
doaj   +1 more source

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