Multi-class clustering of cancer subtypes through SVM based ensemble of pareto-optimal solutions for gene marker identification.
about
A novel biclustering approach to association rule mining for predicting HIV-1-human protein interactions.Identifying Cancer Biomarkers From Microarray Data Using Feature Selection and Semisupervised Learning.Contribution of bioinformatics prediction in microRNA-based cancer therapeutics.In-silico interaction-resolution pathway activity quantification and application to identifying cancer subtypes.Importance of proximity measures in clustering of cancer and miRNA datasets: proposal of an automated framework.Continuity of transcriptomes among colorectal cancer subtypes based on meta-analysis
P2860
Multi-class clustering of cancer subtypes through SVM based ensemble of pareto-optimal solutions for gene marker identification.
description
2010 nî lūn-bûn
@nan
2010 թուականի Նոյեմբերին հրատարակուած գիտական յօդուած
@hyw
2010 թվականի նոյեմբերին հրատարակված գիտական հոդված
@hy
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
name
Multi-class clustering of canc ...... or gene marker identification.
@ast
Multi-class clustering of canc ...... or gene marker identification.
@en
type
label
Multi-class clustering of canc ...... or gene marker identification.
@ast
Multi-class clustering of canc ...... or gene marker identification.
@en
prefLabel
Multi-class clustering of canc ...... or gene marker identification.
@ast
Multi-class clustering of canc ...... or gene marker identification.
@en
P2860
P50
P1433
P1476
Multi-class clustering of canc ...... or gene marker identification.
@en
P2860
P304
P356
10.1371/JOURNAL.PONE.0013803
P407
P577
2010-11-12T00:00:00Z