Suchergebnisse - "Augmented covariant-discriminant algorithm"

Learning protein multi-view features in complex space.

Autoren: Yu, Dong-Jun Hu, Jun Wu, Xiao-Wei et al.

Quelle: Amino Acids; May2013, Vol. 44 Issue 5, p1365-1379, 15p, 1 Diagram, 5 Charts, 7 Graphs

Schlagwörter: AMINO acid sequence, BIOINFORMATICS, MACHINE learning, ALGORITHMS, FEATURE extraction, PROTEIN structure

An information-theoretic approach to the prediction of protein structural class.

Autoren: XIAOQI ZHENG CHUN LI JUN WANG

Quelle: Journal of Computational Chemistry; 4/30/2010, Vol. 31 Issue 6, p1201-1206, 6p, 3 Charts, 2 Graphs

Schlagwörter: PROTEIN engineering, JACKKNIFE (Statistics), RESAMPLING (Statistics), CHEMICAL modification of proteins, AMINO acid sequence

Prediction of protein structural class using a complexity-based distance measure.

Autoren: Taigang Liu Xiaoqi Zheng Jun Wang

Quelle: Amino Acids; Mar2010, Vol. 38 Issue 3, p721-728, 8p, 4 Charts, 1 Graph

Schlagwörter: PROTEIN folding, PROTEIN conformation, AMINO acid sequence, AMINO acid analysis, NEAREST neighbor analysis (Statistics), JACKKNIFE (Statistics)

Using grey dynamic modeling and pseudo amino acid composition to predict protein structural classes.

Autoren: Xuan Xiao Wei-Zhong Lin Kuo-Chen Chou

Quelle: Journal of Computational Chemistry; 2008, Vol. 29 Issue 12, p2018-2024, 7p, 1 Diagram, 3 Charts

Schlagwörter: AMINO acids, PROTEINS, MOLECULAR structure, CHEMICAL structure, SIMULATION methods & models

Using pseudo amino acid composition to predict transmembrane regions in protein: cellular automata and Lempel-Ziv complexity.

Autoren: D. Ma J. Yin J. Xiang

Quelle: Amino Acids; Jan2008, Vol. 34 Issue 1, p111-117, 7p

Schlagwörter: PROTEINS, TOPOLOGY, AMINO acids, MEDICAL research

Using cellular automata images and pseudo amino acid composition to predict protein subcellular location.

Autoren: X. Xiao S. Shao Y. Ding et al.

Quelle: Amino Acids; Feb2006, Vol. 30 Issue 1, p49-54, 6p

Using pseudo amino acid composition to predict protein subcellular location: Approached with Lyapunov index, Bessel function, and Chebyshev filter.

Autoren: Y. Gao S. Shao X. Xiao et al.

Quelle: Amino Acids; Jun2005, Vol. 28 Issue 4, p373-376, 4p

Schlagwörter: AMINO acids, AMINO acid sequence, HANKEL functions, HEREDITY

Using complexity measure factor to predict protein subcellular location.

Autoren: X. Xiao S. Shao Y. Ding et al.

Quelle: Amino Acids; Feb2005, Vol. 28 Issue 1, p57-61, 73p

Schlagwörter: PROTEIN analysis, AMINO acids, AMINO acid sequence, MOLECULAR biology

Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes.

Autoren: Kuo-Chen Chou

Quelle: Bioinformatics; Jan2005, Vol. 21 Issue 1, p10-19, 10p

Prediction of Protein Subcellular Locations by Incorporating Quasi-Sequence-Order Effect

Autoren: Kuo-Chen Chou

Quelle: Biochemical and Biophysical Research Communications. 278:477-483

Schlagwörter: 0301 basic medicine, 0303 health sciences, 03 medical and health sciences, Proteins, Algorithms, Subcellular Fractions

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/11097861
https://www.sciencedirect.com/science/article/pii/S0006291X00938154
https://pubmed.ncbi.nlm.nih.gov/11097861/
https://www.ncbi.nlm.nih.gov/pubmed/11097861
https://europepmc.org/article/MED/11097861

Application of Pseudo Amino Acid Composition for Predicting Protein Subcellular Location: Stochastic Signal Processing Approach.

Autoren: Yu-Xi Pan Zhi-Zhou Zhang Zong-Ming Guo et al.

Quelle: Journal of Protein Chemistry; May2003, Vol. 22 Issue 4, p395-402, 8p

Schlagwörter: PROTEOMICS, MOLECULAR biology, HUMAN genome, BIOINFORMATICS, PROTEINS, GENOMES

Machine Learning Model for Identifying Antioxidant Proteins Using Features Calculated from Primary Sequences.

Autoren: Ho Thanh Lam, Luu Le, Ngoc Hoang Van Tuan, Le et al.

Quelle: Biology (2079-7737); Oct2020, Vol. 9 Issue 10, p325-325, 1p

Schlagwörter: REACTIVE oxygen species, MACHINE learning, PROTEOMICS, ANTIOXIDANTS