Genetic programming for creating Chou's pseudo amino acid based features for submitochondria localization.
about
A new method for predicting the subcellular localization of eukaryotic proteins with both single and multiple sites: Euk-mPLoc 2.0Prediction of antimicrobial peptides based on sequence alignment and feature selection methodsiNR-PhysChem: a sequence-based predictor for identifying nuclear receptors and their subfamilies via physical-chemical property matrixPredicting secretory proteins of malaria parasite by incorporating sequence evolution information into pseudo amino acid composition via grey system modeliGPCR-drug: a web server for predicting interaction between GPCRs and drugs in cellular networkingiCTX-type: a sequence-based predictor for identifying the types of conotoxins in targeting ion channelsiEzy-drug: a web server for identifying the interaction between enzymes and drugs in cellular networkingA multi-label predictor for identifying the subcellular locations of singleplex and multiplex eukaryotic proteinsiSS-PseDNC: identifying splicing sites using pseudo dinucleotide composition.Gene ontology based transfer learning for protein subcellular localizationiDNA-Prot|dis: identifying DNA-binding proteins by incorporating amino acid distance-pairs and reduced alphabet profile into the general pseudo amino acid compositionPredicting protein folding rates using the concept of Chou's pseudo amino acid composition.Mathematical Modeling of Intestinal Iron Absorption Using Genetic Programming.iRSpot-PseDNC: identify recombination spots with pseudo dinucleotide compositionRecombination spot identification Based on gapped k-mers.Naïve Bayes classifier with feature selection to identify phage virion proteinsSubMito-PSPCP: predicting protein submitochondrial locations by hybridizing positional specific physicochemical properties with pseudoamino acid compositionsiRSpot-TNCPseAAC: identify recombination spots with trinucleotide composition and pseudo amino acid componentsPseAAC-General: fast building various modes of general form of Chou's pseudo-amino acid composition for large-scale protein datasets.iNR-Drug: predicting the interaction of drugs with nuclear receptors in cellular networking.Recent progress in predicting protein sub-subcellular locations.Protein submitochondrial localization from integrated sequence representation and SVM-based backward feature extraction.Predicting protein submitochondria locations by combining different descriptors into the general form of Chou's pseudo amino acid composition.iPhos-PseEvo: Identifying Human Phosphorylated Proteins by Incorporating Evolutionary Information into General PseAAC via Grey System Theory.Prediction of Protein Submitochondrial Locations by Incorporating Dipeptide Composition into Chou's General Pseudo Amino Acid Composition.Identification of protein-protein binding sites by incorporating the physicochemical properties and stationary wavelet transforms into pseudo amino acid composition.DSPMP: Discriminating secretory proteins of malaria parasite by hybridizing different descriptors of Chou's pseudo amino acid patterns.Identification of bacteriophage virion proteins by the ANOVA feature selection and analysis.Prediction of protein S-nitrosylation sites based on adapted normal distribution bi-profile Bayes and Chou's pseudo amino acid composition.repRNA: a web server for generating various feature vectors of RNA sequences.PseDNA-Pro: DNA-Binding Protein Identification by Combining Chou's PseAAC and Physicochemical Distance Transformation.Protein classification combining surface analysis and primary structure.Identification of DNA-binding proteins by incorporating evolutionary information into pseudo amino acid composition via the top-n-gram approach.pLoc-mHum: predict subcellular localization of multi-location human proteins via general PseAAC to winnow out the crucial GO information.iPromoter-2L: a two-layer predictor for identifying promoters and their types by multi-window-based PseKNC.Predicting Protein Submitochondrial Locations: The 10th Anniversary.Mito-GSAAC: mitochondria prediction using genetic ensemble classifier and split amino acid composition.iLoc-Animal: a multi-label learning classifier for predicting subcellular localization of animal proteins.Protein remote homology detection by combining Chou's distance-pair pseudo amino acid composition and principal component analysis.Using over-represented tetrapeptides to predict protein submitochondria locations.
P2860
Q21562645-8F21A2D5-7F00-457A-B72D-2813AE41F039Q28477742-A572613F-92F8-4C6C-9861-FBBB3FAF962CQ28480984-658CEFF3-C75A-4202-8860-D4702796026DQ28485324-D4380546-ABBE-4913-940A-A85A4DEB2A3AQ28535719-D3B7F049-BFC7-4785-9FF2-72AE153F7375Q28658162-6CC4A4B1-96F5-4FD0-991C-29D85C950B44Q28661179-292A5602-9576-4F1C-8253-6885785B0FBDQ28729737-F8A28E53-6883-42D7-83DD-382C5DFA8472Q33747883-9484E48F-0959-4E6D-BEBA-F2A1E4DCAA77Q33810069-657334D7-D9E4-493F-BBE1-333F9E1BCB77Q34128762-AF58009F-BC69-4F15-9FD8-9D1292CCF292Q34165172-E3DD47E7-7AE0-45F9-A6AA-F0A69AF695A4Q36245615-1367A909-1FDF-4CD8-9F18-57088BAF043DQ36740900-4EC17E11-2A01-4E2A-9931-0FE1D3F611CAQ36748392-2D3C9825-E689-4BC6-A517-4AE6C02ABF07Q36898465-79A5BBA2-9132-43A7-B484-EF497A19BE95Q37148566-30572015-7754-494A-B14E-4C377161EEE1Q37645097-E1AFA78C-693F-4D83-9463-A95333B19FDBQ37683961-8F288C6A-DA11-4F63-B180-2860D5C91D19Q37684124-42213691-703E-446B-8549-DF45BFCDFC55Q37890426-D2B7EA07-D925-4818-8F4A-9E939B9407D3Q38471324-3C5EA0D6-BC1D-4BCC-9745-18565F588851Q38499799-7CA1CEF4-EB5E-48E1-8963-2B7D7F4671DFQ38794654-4740535F-44C5-4FEF-8CE8-5D3AEDBF4435Q38922819-6F3275B3-CBEA-4081-913D-56F7E3D2219BQ40534208-9467EA3F-7705-4378-AC1C-B67EE881A208Q40944129-781D0174-2F63-4F69-9915-1F71C3522F86Q42212353-751CABE1-4A1D-469A-9466-A717919287B0Q42737215-5037C3C2-CEC7-452E-A10B-1C1D27681293Q45954150-46B7AC4D-B1C9-452D-B425-D794592D2CA5Q45955470-7733AF1F-4652-4ABE-AA78-F8E40975E962Q46418613-C89FCA5B-8796-4187-9C1C-BDA8AFE2ABACQ46834389-0F978EB8-7C2F-4A4B-8814-5A32E32450C0Q47309310-6CA38F7A-BFAC-411E-BC49-5D7211B4DE92Q47316901-7E47265D-F97F-4175-9FC3-4F89EAD6E4DAQ47590186-F1972D92-A12C-452A-983D-4B30CE714B3DQ47976401-E65B9B83-BF83-440F-93DD-2A34D9F996A2Q50761949-4A79F268-CC7F-4354-93BE-400093642912Q50927764-AEDFD7E2-2B84-425D-AB7B-7AB92632A340Q51247652-C7C2E62D-0049-4524-A49F-27FC60D23A54
P2860
Genetic programming for creating Chou's pseudo amino acid based features for submitochondria localization.
description
2008 nî lūn-bûn
@nan
2008 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2008 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2008年の論文
@ja
2008年論文
@yue
2008年論文
@zh-hant
2008年論文
@zh-hk
2008年論文
@zh-mo
2008年論文
@zh-tw
2008年论文
@wuu
name
Genetic programming for creati ...... submitochondria localization.
@ast
Genetic programming for creati ...... submitochondria localization.
@en
Genetic programming for creati ...... submitochondria localization.
@nl
type
label
Genetic programming for creati ...... submitochondria localization.
@ast
Genetic programming for creati ...... submitochondria localization.
@en
Genetic programming for creati ...... submitochondria localization.
@nl
prefLabel
Genetic programming for creati ...... submitochondria localization.
@ast
Genetic programming for creati ...... submitochondria localization.
@en
Genetic programming for creati ...... submitochondria localization.
@nl
P1433
P1476
Genetic programming for creati ...... submitochondria localization.
@en
P2093
Loris Nanni
P2888
P304
P356
10.1007/S00726-007-0018-1
P577
2008-01-04T00:00:00Z