Piecewise-constant and low-rank approximation for identification of recurrent copy number variations.
about
A novel network regularized matrix decomposition method to detect mutated cancer genes in tumour samples with inter-patient heterogeneity.Fast dimension reduction and integrative clustering of multi-omics data using low-rank approximation: application to cancer molecular classification.Penalized weighted low-rank approximation for robust recovery of recurrent copy number variations.Discovering potential driver genes through an integrated model of somatic mutation profiles and gene functional information.
P2860
Piecewise-constant and low-rank approximation for identification of recurrent copy number variations.
description
2014 nî lūn-bûn
@nan
2014年の論文
@ja
2014年学术文章
@wuu
2014年学术文章
@zh
2014年学术文章
@zh-cn
2014年学术文章
@zh-hans
2014年学术文章
@zh-my
2014年学术文章
@zh-sg
2014年學術文章
@yue
2014年學術文章
@zh-hant
name
Piecewise-constant and low-ran ...... urrent copy number variations.
@en
Piecewise-constant and low-ran ...... urrent copy number variations.
@nl
type
label
Piecewise-constant and low-ran ...... urrent copy number variations.
@en
Piecewise-constant and low-ran ...... urrent copy number variations.
@nl
prefLabel
Piecewise-constant and low-ran ...... urrent copy number variations.
@en
Piecewise-constant and low-ran ...... urrent copy number variations.
@nl
P2860
P356
P1433
P1476
Piecewise-constant and low-ran ...... current copy number variations
@en
P2093
Xiaowei Zhou
P2860
P304
P356
10.1093/BIOINFORMATICS/BTU131
P407
P577
2014-03-17T00:00:00Z