A data similarity-based strategy for meta-analysis of transcriptional profiles in cancer.
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Evaluation of public cancer datasets and signatures identifies TP53 mutant signatures with robust prognostic and predictive valueA Murine Model of K-RAS and β-Catenin Induced Renal Tumors Expresses High Levels of E2F1 and Resembles Human Wilms TumorSPARCL1 suppresses metastasis in prostate cancer.Identification of a gene-expression predictor for diagnosis and personalized stratification of lupus patients.
P2860
A data similarity-based strategy for meta-analysis of transcriptional profiles in cancer.
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2013 nî lūn-bûn
@nan
2013 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2013 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2013年の論文
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2013年論文
@yue
2013年論文
@zh-hant
2013年論文
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2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
name
A data similarity-based strategy for meta-analysis of transcriptional profiles in cancer.
@ast
A data similarity-based strategy for meta-analysis of transcriptional profiles in cancer.
@en
type
label
A data similarity-based strategy for meta-analysis of transcriptional profiles in cancer.
@ast
A data similarity-based strategy for meta-analysis of transcriptional profiles in cancer.
@en
prefLabel
A data similarity-based strategy for meta-analysis of transcriptional profiles in cancer.
@ast
A data similarity-based strategy for meta-analysis of transcriptional profiles in cancer.
@en
P2093
P2860
P1433
P1476
A data similarity-based strategy for meta-analysis of transcriptional profiles in cancer.
@en
P2093
Alfred L George
Daniel Joseph Viox
Pengcheng Lu
Qingchao Qiu
Yuzhu Xiang
P2860
P304
P356
10.1371/JOURNAL.PONE.0054979
P407
P577
2013-01-29T00:00:00Z