A Comparative Study on Filtering Protein Secondary Structure Prediction

被引：15

作者：

Kountouris, Petros ^{[1
]}

Agathocleous, Michalis ^{[1
]}

Promponas, Vasilis J. ^{[2
]}

Christodoulou, Georgia ^{[1
]}

Hadjicostas, Simos ^{[1
]}

Vassiliades, Vassilis ^{[1
]}

Christodoulou, Chris ^{[1
]}

机构：

[1] Univ Cyprus, Dept Comp Sci, CY-1678 Nicosia, Cyprus

[2] Univ Cyprus, Dept Biol Sci, CY-1678 Nicosia, Cyprus

来源：

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS | 2012年 / 9卷 / 03期

关键词：

Protein secondary structure prediction; filtering; machine learning; structural bioinformatics; bidirectional recurrent neural networks; MULTIPLE LINEAR-REGRESSION; RECURRENT NEURAL-NETWORKS; DIHEDRAL ANGLES; PSI-BLAST; INFORMATION; ALGORITHM; ACCURACY; MATRICES; DATABASE; SERVER;

D O I：

10.1109/TCBB.2012.22

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Filtering of Protein Secondary Structure Prediction (PSSP) aims to provide physicochemically realistic results, while it usually improves the predictive performance. We performed a comparative study on this challenging problem, utilizing both machine learning techniques and empirical rules and we found that combinations of the two lead to the highest improvement.

引用

页码：731 / 739

页数：9

共 50 条

[21] Empirical Study of Protein Feature Representation on Deep Belief Networks Trained With Small Data for Secondary Structure Prediction
Rashid, Shamima
Sundaram, Suresh
Kwoh, Chee Keong
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2023, 20 (02) : 955 - 966
[22] Context-Based Features Enhance Protein Secondary Structure Prediction Accuracy
Yaseen, Ashraf
Li, Yaohang
JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2014, 54 (03) : 992 - 1002
[23] Fast learning optimized prediction methodology (FLOPRED) for protein secondary structure prediction
S. Saraswathi
J. L. Fernández-Martínez
A. Kolinski
R. L. Jernigan
A. Kloczkowski
Journal of Molecular Modeling, 2012, 18 : 4275 - 4289
[24] Fast learning optimized prediction methodology (FLOPRED) for protein secondary structure prediction
Saraswathi, S.
Fernandez-Martinez, J. L.
Kolinski, A.
Jernigan, R. L.
Kloczkowski, A.
JOURNAL OF MOLECULAR MODELING, 2012, 18 (09) : 4275 - 4289
[25] Protein Secondary Structure Prediction Using Support Vector Machines and a Codon Encoding Scheme
Zamani, Masood
Kremer, Stefan C.
2012 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE WORKSHOPS (BIBMW), 2012,
[26] Using evolutionary trees in protein secondary structure prediction and other comparative sequence analyses
Goldman, N
Thorne, JL
Jones, DT
JOURNAL OF MOLECULAR BIOLOGY, 1996, 263 (02) : 196 - 208
[27] Cascading Discriminant and Generative Models for Protein Secondary Structure Prediction
Thomarat, Fabienne
Lauer, Fabien
Guermeur, Yann
PATTERN RECOGNITION IN BIOINFORMATICS, 2012, 7632 : 166 - 177
[28] JPred4: a protein secondary structure prediction server
Drozdetskiy, Alexey
Cole, Christian
Procter, James
Barton, Geoffrey J.
NUCLEIC ACIDS RESEARCH, 2015, 43 (W1) : W389 - W394
[29] HYBRID SYSTEM FOR PROTEIN SECONDARY STRUCTURE PREDICTION
ZHANG, X
MESIROV, JP
WALTZ, DL
JOURNAL OF MOLECULAR BIOLOGY, 1992, 225 (04) : 1049 - 1063
[30] Combining Classifiers for Protein Secondary Structure Prediction
Aydin, Zafer
Uzut, Ommu Gulsum
2017 9TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMMUNICATION NETWORKS (CICN), 2017, : 29 - 33

← 1 2 3 4 5 →