A feature extraction technique using bi-gram probabilities of position specific scoring matrix for protein fold recognition.
about
Recent Progress in Machine Learning-Based Methods for Protein Fold RecognitionDisPredict: A Predictor of Disordered Protein Using Optimized RBF KernelA strategy to select suitable physicochemical attributes of amino acids for protein fold recognition.Proposing a highly accurate protein structural class predictor using segmentation-based features.Estimation of Position Specific Energy as a Feature of Protein Residues from Sequence Alone for Structural ClassificationAn ensemble approach to protein fold classification by integration of template-based assignment and support vector machine classifier.Protein fold recognition using geometric kernel data fusion.A Novel Feature Extraction Method with Feature Selection to Identify Golgi-Resident Protein Types from Imbalanced DataImproving protein fold recognition using the amalgamation of evolutionary-based and structural based information.Evaluation of sequence features from intrinsically disordered regions for the estimation of protein function.Prediction of aptamer-protein interacting pairs using an ensemble classifier in combination with various protein sequence attributesPredicting MoRFs in protein sequences using HMM profiles.ProFold: Protein Fold Classification with Additional Structural Features and a Novel Ensemble ClassifierIdentification of self-interacting proteins by exploring evolutionary information embedded in PSI-BLAST-constructed position specific scoring matrix.An improved method for predicting interactions between virus and human proteins.Screening drug-target interactions with positive-unlabeled learningImproving protein-protein interactions prediction accuracy using protein evolutionary information and relevance vector machine model.Protein folds recognized by an intelligent predictor based-on evolutionary and structural information.Structural classification of proteins using texture descriptors extracted from the cellular automata image.HMMBinder: DNA-Binding Protein Prediction Using HMM Profile Based Features.iDNAProt-ES: Identification of DNA-binding Proteins Using Evolutionary and Structural Features.Success: evolutionary and structural properties of amino acids prove effective for succinylation site prediction.Detection of Interactions between Proteins by Using Legendre Moments Descriptor to Extract Discriminatory Information Embedded in PSSM.Prediction of Drug-Target Interaction Networks from the Integration of Protein Sequences and Drug Chemical Structures.Improving succinylation prediction accuracy by incorporating the secondary structure via helix, strand and coil, and evolutionary information from profile bigrams.Detecting Succinylation sites from protein sequences using ensemble support vector machine.An empirical study of different approaches for protein classificationAccurate Prediction of ncRNA-Protein Interactions From the Integration of Sequence and Evolutionary Information
P2860
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P2860
A feature extraction technique using bi-gram probabilities of position specific scoring matrix for protein fold recognition.
description
2012 nî lūn-bûn
@nan
2012 թուականի Դեկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2012 թվականի դեկտեմբերին հրատարակված գիտական հոդված
@hy
2012年の論文
@ja
2012年論文
@yue
2012年論文
@zh-hant
2012年論文
@zh-hk
2012年論文
@zh-mo
2012年論文
@zh-tw
2012年论文
@wuu
name
A feature extraction technique ...... for protein fold recognition.
@ast
A feature extraction technique ...... for protein fold recognition.
@en
type
label
A feature extraction technique ...... for protein fold recognition.
@ast
A feature extraction technique ...... for protein fold recognition.
@en
prefLabel
A feature extraction technique ...... for protein fold recognition.
@ast
A feature extraction technique ...... for protein fold recognition.
@en
P2093
P1476
A feature extraction technique ...... x for protein fold recognition
@en
P2093
Abdollah Dehzangi
James Lyons
Kuldip K Paliwal
P356
10.1016/J.JTBI.2012.12.008
P407
P50
P577
2012-12-13T00:00:00Z