iATC-mISF: a multi-label classifier for predicting the classes of anatomical therapeutic chemicals.
about
Predicting antimicrobial peptides with improved accuracy by incorporating the compositional, physico-chemical and structural features into Chou's general PseAAC.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 networkPrediction of presynaptic and postsynaptic neurotoxins by combining various Chou's pseudo components.Genome-Wide Prediction of DNA Methylation Using DNA Composition and Sequence Complexity in HumanA computational method for the identification of candidate drugs for non-small cell lung cancer.Small molecular floribundiquinone B derived from medicinal plants inhibits acetylcholinesterase activity.Prediction of the aquatic toxicity of aromatic compounds to tetrahymena pyriformis through support vector regression.iATC-mHyb: a hybrid multi-label classifier for predicting the classification of anatomical therapeutic chemicals.iRNA-PseColl: Identifying the Occurrence Sites of Different RNA Modifications by Incorporating Collective Effects of Nucleotides into PseKNC.A novel feature ranking method for prediction of cancer stages using proteomics data.2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications.MLACP: machine-learning-based prediction of anticancer peptides.Evolutionary mechanism and biological functions of 8-mers containing CG dinucleotide in yeast.Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate.iDNAProt-ES: Identification of DNA-binding Proteins Using Evolutionary and Structural Features.Prediction of HIV-1 and HIV-2 proteins by using Chou's pseudo amino acid compositions and different classifiers.DHSpred: support-vector-machine-based human DNase I hypersensitive sites prediction using the optimal features selected by random forest.The Comparative Experimental Study of Multilabel Classification for Diagnosis Assistant Based on Chinese Obstetric EMRs.Implications of Newly Identified Brain eQTL Genes and Their Interactors in Schizophrenia.PseUI: Pseudouridine sites identification based on RNA sequence informationA Comprehensive In Silico Method to Study the QSTR of the Aconitine Alkaloids for Designing Novel Drugs
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P2860
iATC-mISF: a multi-label classifier for predicting the classes of anatomical therapeutic chemicals.
description
2017 nî lūn-bûn
@nan
2017年の論文
@ja
2017年学术文章
@wuu
2017年学术文章
@zh-cn
2017年学术文章
@zh-hans
2017年学术文章
@zh-my
2017年学术文章
@zh-sg
2017年學術文章
@yue
2017年學術文章
@zh
2017年學術文章
@zh-hant
name
iATC-mISF: a multi-label class ...... tomical therapeutic chemicals.
@en
type
label
iATC-mISF: a multi-label class ...... tomical therapeutic chemicals.
@en
prefLabel
iATC-mISF: a multi-label class ...... tomical therapeutic chemicals.
@en
P2860
P356
P1433
P1476
iATC-mISF: a multi-label class ...... tomical therapeutic chemicals.
@en
P2093
Shu-Guang Zhao
Xiang Cheng
P2860
P304
P356
10.1093/BIOINFORMATICS/BTW644
P407
P577
2017-02-01T00:00:00Z