Related references
Note: Only part of the references are listed.iCarPS: a computational tool for identifying protein carbonylation sites by novel encoded features
Dan Zhang et al.
BIOINFORMATICS (2021)
RaacLogo: a new sequence logo generator by using reduced amino acid clusters
Lei Zheng et al.
BRIEFINGS IN BIOINFORMATICS (2021)
Multi-substrate selectivity based on key loops and non-homologous domains: new insight into ALKBH family
Baofang Xu et al.
CELLULAR AND MOLECULAR LIFE SCIENCES (2021)
Modular arrangements of sequence motifs determine the functional diversity of KDM proteins
Zerong Wang et al.
BRIEFINGS IN BIOINFORMATICS (2021)
Design powerful predictor for mRNA subcellular location prediction in Homo sapiens
Zhao-Yue Zhang et al.
BRIEFINGS IN BIOINFORMATICS (2021)
StackCPPred: a stacking and pairwise energy content-based prediction of cell-penetrating peptides and their uptake efficiency
Xiangzheng Fu et al.
BIOINFORMATICS (2020)
PPTPP: a novel therapeutic peptide prediction method using physicochemical property encoding and adaptive feature representation learning
Yu P. Zhang et al.
BIOINFORMATICS (2020)
CWLy-SVM: A support vector machine-based tool for identifying cell wall lytic enzymes
Chaolu Meng et al.
COMPUTATIONAL BIOLOGY AND CHEMISTRY (2020)
Predicting Preference of Transcription Factors for Methylated DNA Using Sequence Information
Meng-Lu Liu et al.
MOLECULAR THERAPY-NUCLEIC ACIDS (2020)
Prediction of N7-methylguanosine sites in human RNA based on optimal sequence features
Yu-He Yang et al.
GENOMICS (2020)
Amino Acid k-mer Feature Extraction for Quantitative Antimicrobial Resistance (AMR) Prediction by Machine Learning and Model Interpretation for Biological Insights
Taha ValizadehAslani et al.
BIOLOGY-BASEL (2020)
Function determinants of TET proteins: the arrangements of sequence motifs with specific codes
Dongyang Liu et al.
BRIEFINGS IN BIOINFORMATICS (2019)
Characterization of proteins in different subcellular localizations for Escherichia coli K12
Qi Zhang et al.
GENOMICS (2019)
4mCPred: machine learning methods for DNA N4-methylcytosine sites prediction
Wenying He et al.
BIOINFORMATICS (2019)
Exploring sequence-based features for the improved prediction of DNA N4-methylcytosine sites in multiple species
Leyi Wei et al.
BIOINFORMATICS (2019)
iTerm-PseKNC: a sequence-based tool for predicting bacterial transcriptional terminators
Chao-Qin Feng et al.
BIOINFORMATICS (2019)
Relevance of Machine Learning Techniques and Various Protein Features in Protein Fold Classification: A Review
Komal Patil et al.
CURRENT BIOINFORMATICS (2019)
Using an optimal set of features with a machine learning-based approach to predict effector proteins for Legionella pneumophila
Zhila Esna Ashari et al.
PLOS ONE (2019)
PEPred-Suite: improved and robust prediction of therapeutic peptides using adaptive feature representation learning
Leyi Wei et al.
BIOINFORMATICS (2019)
A Random Forest Sub-Golgi Protein Classifier Optimized via Dipeptide and Amino Acid Composition Features
Zhibin Lv et al.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY (2019)
Identify origin of replication in Saccharomyces cerevisiae using two-step feature selection technique
Fu-Ying Dao et al.
BIOINFORMATICS (2019)
A Brief Survey of Machine Learning Methods in Protein Sub-Golgi Localization
Wuritu Yang et al.
CURRENT BIOINFORMATICS (2019)
A Review on the Recent Developments of Sequence-based Protein Feature Extraction Methods
Jun Zhang et al.
CURRENT BIOINFORMATICS (2019)
A Survey for Predicting Enzyme Family Classes Using Machine Learning Methods
Jiu-Xin Tan et al.
CURRENT DRUG TARGETS (2019)
Predicting protein structural classes for low-similarity sequences by evaluating different features
Xiao-Juan Zhu et al.
KNOWLEDGE-BASED SYSTEMS (2019)
RAACBook: a web server of reduced amino acid alphabet for sequence-dependent inference by using Chou's five-step rule
Lei Zheng et al.
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION (2019)
Identification of hormone binding proteins based on machine learning methods
Jiu-Xin Tan et al.
MATHEMATICAL BIOSCIENCES AND ENGINEERING (2019)
AmPEP: Sequence-based prediction of antimicrobial peptides using distribution patterns of amino acid properties and random forest
Pratiti Bhadra et al.
SCIENTIFIC REPORTS (2018)
SVM-SulfoSite: A support vector machine based predictor for sulfenylation sites
Hussam J. Al-barakati et al.
SCIENTIFIC REPORTS (2018)
Pro54DB: a database for experimentally verified sigma-54 promoters
Zhi-Yong Liang et al.
BIOINFORMATICS (2017)
PseKRAAC: a flexible web server for generating pseudo K-tuple reduced amino acids composition
Yongchun Zuo et al.
BIOINFORMATICS (2017)
GASS-WEB: a web server for identifying enzyme active sites based on genetic algorithms
Joao P. A. Moraes et al.
NUCLEIC ACIDS RESEARCH (2017)
Pretata: predicting TATA binding proteins with novel features and dimensionality reduction strategy
Quan Zou et al.
BMC SYSTEMS BIOLOGY (2016)
Predicting Human Enzyme Family Classes by Using Pseudo Amino Acid Composition
Yun Wu et al.
CURRENT PROTEOMICS (2016)
SuccFind: a novel succinylation sites online prediction tool via enhanced characteristic strategy
Hao-Dong Xu et al.
BIOINFORMATICS (2015)
Amino acid alphabet reduction preserves fold information contained in contact interactions in proteins
Armando D. Solis
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS (2015)
GASS: identifying enzyme active sites with genetic algorithms
Sandro C. Izidoro et al.
BIOINFORMATICS (2015)
iDPF-PseRAAAC: A Web-Server for Identifying the Defensin Peptide Family and Subfamily Using Pseudo Reduced Amino Acid Alphabet Composition
Yongchun Zuo et al.
PLOS ONE (2015)
The value of aspartate aminotransferase and alanine aminotransferase in cardiovascular disease risk assessment
Stephen F. Weng et al.
OPEN HEART (2015)
Human proteins characterization with subcellular localizations
Lei Yang et al.
JOURNAL OF THEORETICAL BIOLOGY (2014)
A similarity distance of diversity measure for discriminating mesophilic and thermophilic proteins
Yong-Chun Zuo et al.
AMINO ACIDS (2013)
ECOH: An Enzyme Commission number predictor using mutual information and a support vector machine
Yoshihiko Matsuta et al.
BIOINFORMATICS (2013)
Accurate prediction of protein enzymatic class by N-to-1 Neural Networks
Viola Volpato et al.
BMC BIOINFORMATICS (2013)
LIBSVM: A Library for Support Vector Machines
Chih-Chung Chang et al.
ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY (2011)
Metric learning for enzyme active-site search
Tsuyoshi Kato et al.
BIOINFORMATICS (2010)
Using the Concept of Chou's Pseudo Amino Acid Composition to Predict Enzyme Family Classes: An Approach with Support Vector Machine Based on Discrete Wavelet Transform
Jian-Ding Qiu et al.
PROTEIN AND PEPTIDE LETTERS (2010)
Using reduced amino acid composition to predict defensin family and subfamily: Integrating similarity measure and structural alphabet
Yong-Chun Zuo et al.
PEPTIDES (2009)
Using Chou's amphiphilic pseudo-amino acid composition and support vector machine for prediction of enzyme subfamily classes
Xi-Bin Zhou et al.
JOURNAL OF THEORETICAL BIOLOGY (2007)
Grouping of amino acid types and extraction of amino acid properties from multiple sequence alignments using variance maximization
JO Wrabl et al.
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS (2005)
Predicting enzyme family classes by hybridizing gene product composition and pseudo-amino acid composition
YD Cai et al.
JOURNAL OF THEORETICAL BIOLOGY (2005)
Adenoviral vector-mediated expression of a gene encoding secreted, EpCAM-targeted carboxylesterase-2 sensitises colon cancer spheroids to CPT-11
D Oosterhoff et al.
BRITISH JOURNAL OF CANCER (2005)
Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes
KC Chou
BIOINFORMATICS (2005)
Predicting enzyme family class in a hybridization space
KC Chou et al.
PROTEIN SCIENCE (2004)
Simplified amino acid alphabets based on deviation of conditional probability from random background
X Liu et al.
PHYSICAL REVIEW E (2002)
Cell surface display of a lysosomal enzyme for extracellular gene-directed enzyme prodrug therapy
D Heine et al.
GENE THERAPY (2001)
Share Paper
