DNA-Prot: identification of DNA binding proteins from protein sequence information using random forest.
about
Predicting secretory proteins of malaria parasite by incorporating sequence evolution information into pseudo amino acid composition via grey system modelIdentification of DNA-binding proteins using support vector machine with sequence informationDNA-protein interactions: methods for detection and analysis.A predicted physicochemically distinct sub-proteome associated with the intracellular organelle of the anammox bacterium Kuenenia stuttgartiensis.enDNA-Prot: identification of DNA-binding proteins by applying ensemble learning.iDNA-Prot: identification of DNA binding proteins using random forest with grey model.iDNA-Prot|dis: identifying DNA-binding proteins by incorporating amino acid distance-pairs and reduced alphabet profile into the general pseudo amino acid compositionIdentifying DNA-binding proteins by combining support vector machine and PSSM distance transformationPredicting DNA-binding proteins and binding residues by complex structure prediction and application to human proteome.ProFET: Feature engineering captures high-level protein functions.Identification of DNA-binding proteins using multi-features fusion and binary firefly optimization algorithm.DNA binding protein identification by combining pseudo amino acid composition and profile-based protein representationDNABP: Identification of DNA-Binding Proteins Based on Feature Selection Using a Random Forest and Predicting Binding Residues.A proposal for the revision of molecular boundary typology.iRSpot-GAEnsC: identifing recombination spots via ensemble classifier and extending the concept of Chou's PseAAC to formulate DNA samples.DNA-binding protein prediction using plant specific support vector machines: validation and application of a new genome annotation tool.PSFM-DBT: Identifying DNA-Binding Proteins by Combing Position Specific Frequency Matrix and Distance-Bigram Transformation.Sequence based prediction of DNA-binding proteins based on hybrid feature selection using random forest and Gaussian naïve Bayes.Improved detection of DNA-binding proteins via compression technology on PSSM information.PseDNA-Pro: DNA-Binding Protein Identification by Combining Chou's PseAAC and Physicochemical Distance Transformation.Classification of large microarray datasets using fast random forest construction.Identification of DNA-binding proteins by incorporating evolutionary information into pseudo amino acid composition via the top-n-gram approach.HMMBinder: DNA-Binding Protein Prediction Using HMM Profile Based Features.iDNAProt-ES: Identification of DNA-binding Proteins Using Evolutionary and Structural Features.Protein sequence comparison and DNA-binding protein identification with generalized PseAAC and graphical representation.A complexity-based method to compare RNA secondary structures and its application.A Model Stacking Framework for Identifying DNA Binding Proteins by Orchestrating Multi-View Features and Classifiers
P2860
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P2860
DNA-Prot: identification of DNA binding proteins from protein sequence information using random forest.
description
2009 nî lūn-bûn
@nan
2009 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2009 թվականի հունիսին հրատարակված գիտական հոդված
@hy
2009年の論文
@ja
2009年学术文章
@wuu
2009年学术文章
@zh-cn
2009年学术文章
@zh-hans
2009年学术文章
@zh-my
2009年学术文章
@zh-sg
2009年學術文章
@yue
name
DNA-Prot: identification of DN ...... formation using random forest.
@ast
DNA-Prot: identification of DN ...... formation using random forest.
@en
type
label
DNA-Prot: identification of DN ...... formation using random forest.
@ast
DNA-Prot: identification of DN ...... formation using random forest.
@en
prefLabel
DNA-Prot: identification of DN ...... formation using random forest.
@ast
DNA-Prot: identification of DN ...... formation using random forest.
@en
P2860
P1476
DNA-Prot: identification of DN ...... formation using random forest.
@en
P2093
K Krishna Kumar
P N Suganthan
P2860
P304
P356
10.1080/07391102.2009.10507281
P577
2009-06-01T00:00:00Z