An integrated genomic-based approach to individualized treatment of patients with advanced-stage ovarian cancer.
about
Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancerOvarian cancer biomarker discovery based on genomic approachesIntegrated genomic analyses of ovarian carcinomaUtilization of genomic signatures to identify phenotype-specific drugsMulti-gene expression predictors of single drug responses to adjuvant chemotherapy in ovarian carcinoma: predicting platinum resistance.Integrated analysis of gene expression and tumor nuclear image profiles associated with chemotherapy response in serous ovarian carcinomaIntegrated analysis of gene expression profiles associated with response of platinum/paclitaxel-based treatment in epithelial ovarian cancerBiasogram: visualization of confounding technical bias in gene expression dataPareto Optimization Identifies Diverse Set of Phosphorylation Signatures Predicting Response to Treatment with DasatinibA reproducible approach to high-throughput biological data acquisition and integrationAngiogenic mRNA and microRNA gene expression signature predicts a novel subtype of serous ovarian cancerUtilizing the molecular gateway: the path to personalized cancer management.Phase II evaluation of dasatinib in the treatment of recurrent or persistent epithelial ovarian or primary peritoneal carcinoma: a Gynecologic Oncology Group study.Chemotherapy intensity and toxicity among black and white women with advanced and recurrent endometrial cancer: a Gynecologic Oncology Group StudyProspective comparison of clinical and genomic multivariate predictors of response to neoadjuvant chemotherapy in breast cancer.Concordant gene expression signatures predict clinical outcomes of cancer patients undergoing systemic therapyGenomancy: predicting tumour response to cancer therapy based on the oracle of genetics.A strategy for predicting the chemosensitivity of human cancers and its application to drug discoveryPhosphosignature predicts dasatinib response in non-small cell lung cancer.Pathway-based classification of cancer subtypes.curatedOvarianData: clinically annotated data for the ovarian cancer transcriptomeMeta-analysis of microarray data identifies GAS6 expression as an independent predictor of poor survival in ovarian cancerMás-o-menos: a simple sign averaging method for discrimination in genomic data analysis.CCND1 as a predictive biomarker of neoadjuvant chemotherapy in patients with locally advanced head and neck squamous cell carcinoma.Structured Matrix Completion with Applications to Genomic Data Integration.Microarray analysis of RNA extracted from formalin-fixed, paraffin-embedded and matched fresh-frozen ovarian adenocarcinomas.Integrated analysis of DNA methylation and gene expression reveals specific signaling pathways associated with platinum resistance in ovarian cancerGene expression profile for predicting survival in advanced-stage serous ovarian cancer across two independent datasets.Analysis of multiple sarcoma expression datasets: implications for classification, oncogenic pathway activation and chemotherapy resistanceTime-dependent transcriptional profiling links gene expression to mitogen-activated protein kinase kinase 4 (MKK4)-mediated suppression of omental metastatic colonization.Latent factor analysis to discover pathway-associated putative segmental aneuploidies in human cancers.Identification of differentially expressed genes using an annealing control primer system in stage III serous ovarian carcinoma.Survival prediction based on inherited gene variation analysisUtility of functional imaging in prediction or assessment of treatment response and prognosis following thermotherapy.Integrated analysis of multiple microarray datasets identifies a reproducible survival predictor in ovarian cancer.Microarray-based oncogenic pathway profiling in advanced serous papillary ovarian carcinoma.A comparative study on gene-set analysis methods for assessing differential expression associated with the survival phenotypeCurrent and future applications of toxicogenomics: Results summary of a survey from the HESI Genomics State of Science SubcommitteeTime to recurrence and survival in serous ovarian tumors predicted from integrated genomic profiles.Copy number variation analysis of matched ovarian primary tumors and peritoneal metastasis
P2860
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P2860
An integrated genomic-based approach to individualized treatment of patients with advanced-stage ovarian cancer.
description
2007 nî lūn-bûn
@nan
2007年の論文
@ja
2007年論文
@yue
2007年論文
@zh-hant
2007年論文
@zh-hk
2007年論文
@zh-mo
2007年論文
@zh-tw
2007年论文
@wuu
2007年论文
@zh
2007年论文
@zh-cn
name
An integrated genomic-based ap ...... advanced-stage ovarian cancer.
@en
type
label
An integrated genomic-based ap ...... advanced-stage ovarian cancer.
@en
prefLabel
An integrated genomic-based ap ...... advanced-stage ovarian cancer.
@en
P2093
P356
P1476
An integrated genomic-based ap ...... advanced-stage ovarian cancer
@en
P2093
Andrea Bild
Andrew Berchuck
Anil Potti
Geoffrey S Ginsburg
Holly K Dressman
Janiel Cragun
Jeffrey Marks
Johnathan M Lancaster
Jonathan Gray
P304
P356
10.1200/JCO.2006.06.3743
P407
P577
2007-02-01T00:00:00Z