Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.
about
Comparative analysis of genes frequently regulated by drugs based on connectivity map transcriptome data.Relevance popularity: A term event model based feature selection scheme for text classification.An integrated method for the identification of novel genes related to oral cancerOmniGA: Optimized Omnivariate Decision Trees for Generalizable Classification Models.Sequence-based predictive modeling to identify cancerlectins.
P2860
Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.
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
Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.
@en
Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.
@nl
type
label
Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.
@en
Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.
@nl
prefLabel
Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.
@en
Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.
@nl
P2860
P50
P356
P1476
Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.
@en
P2093
P2860
P304
P356
10.1155/2016/7604641
P577
2016-07-13T00:00:00Z