articleTop 1% cited
Some remarks on protein attribute prediction and pseudo amino acid composition
Journal of Theoretical Biology · 2010 · Vol. 273(1) · pp. 236–247
Kuo‐Chen Chou✉(The Gordon Life Science Institute)
Machine Learning in BioinformaticsGenomics and Phylogenetic StudiesProtein Structure and DynamicsPseudo amino acid compositionComputer scienceBenchmark (surveying)Protein sequencingSequence (biology)Computational biologyPaceData miningBiologyPeptide sequence
MeSH terms
AlgorithmsAmino AcidsHumansProteinsReproducibility of ResultsProtein Structure, SecondaryProtein Structure, TertiaryEvolution, MolecularInternetSequence Analysis, ProteinDatabases, Protein
Citations
1,245
FWCI
29.08
field-weighted impact
References
225
Percentile
100%
vs. same field & year
Citations per year
Cited by
iACP: a sequence-based tool for identifying anticancer peptides
Oncotarget · 2016 · 433 citations
References
On the generalized distance in statistics
SHILAP Revista de lepidopterología · 1936 · 5,968 citations
Euk-mPLoc: A Fusion Classifier for Large-Scale Eukaryotic Protein Subcellular Location Prediction by Incorporating Multiple Sites
Journal of Proteome Research · 2007 · 327 citations
SCOP: A structural classification of proteins database for the investigation of sequences and structures
Journal of Molecular Biology · 1995 · 6,318 citations
Gene Ontology: tool for the unification of biology
Nature Genetics · 2000 · 43,975 citations
Nearest neighbor pattern classification
IEEE Transactions on Information Theory · 1967 · 15,642 citations
Prediction of protein cellular attributes using pseudo‐amino acid composition
Proteins Structure Function and Bioinformatics · 2001 · 1,958 citations
The COG database: an updated version includes eukaryotes
BMC Bioinformatics · 2003 · 4,484 citations
Related articles
Prediction of protein cellular attributes using pseudo‐amino acid composition
Proteins Structure Function and Bioinformatics · 2001 · 1,958 citations
Citation Network
How this paper connects to the literature. Drag to explore, click any node to open that paper.
