iPhos-PseEvo: Identifying Human Phosphorylated Proteins by Incorporating Evolutionary Information into General PseAAC via Grey System Theory.
about
2L-piRNA: A Two-Layer Ensemble Classifier for Identifying Piwi-Interacting RNAs and Their Function.Molecular classification of prostate adenocarcinoma by the integrated somatic mutation profiles and molecular networkiPTM-mLys: identifying multiple lysine PTM sites and their different types.ProFold: Protein Fold Classification with Additional Structural Features and a Novel Ensemble ClassifierGenome-Wide Prediction of DNA Methylation Using DNA Composition and Sequence Complexity in HumanpSumo-CD: predicting sumoylation sites in proteins with covariance discriminant algorithm by incorporating sequence-coupled effects into general PseAAC.Imbalanced multi-label learning for identifying antimicrobial peptides and their functional types.iRNAm5C-PseDNC: identifying RNA 5-methylcytosine sites by incorporating physical-chemical properties into pseudo dinucleotide compositioniRNA-PseColl: Identifying the Occurrence Sites of Different RNA Modifications by Incorporating Collective Effects of Nucleotides into PseKNC.Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate.Detection of Interactions between Proteins by Using Legendre Moments Descriptor to Extract Discriminatory Information Embedded in PSSM.iMulti-HumPhos: a multi-label classifier for identifying human phosphorylated proteins using multiple kernel learning based support vector machines.Prediction of HIV-1 and HIV-2 proteins by using Chou's pseudo amino acid compositions and different classifiers.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.Implications of Newly Identified Brain eQTL Genes and Their Interactors in Schizophrenia.The analysis of GM (1, 1) grey model to predict the incidence trend of typhoid and paratyphoid fevers in Wuhan City, China
P2860
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P2860
iPhos-PseEvo: Identifying Human Phosphorylated Proteins by Incorporating Evolutionary Information into General PseAAC via Grey System Theory.
description
2016 nî lūn-bûn
@nan
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
2016年论文
@zh
2016年论文
@zh-cn
name
iPhos-PseEvo: Identifying Huma ...... PseAAC via Grey System Theory.
@en
type
label
iPhos-PseEvo: Identifying Huma ...... PseAAC via Grey System Theory.
@en
prefLabel
iPhos-PseEvo: Identifying Huma ...... PseAAC via Grey System Theory.
@en
P2093
P2860
P356
P1476
iPhos-PseEvo: Identifying Huma ...... PseAAC via Grey System Theory.
@en
P2093
Bi-Qian Sun
Wang-Ren Qiu
P2860
P356
10.1002/MINF.201600010
P577
2016-05-12T00:00:00Z