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Driver pattern identification over the gene co-expression of drug response in ovarian cancer by integrating high throughput genomics data

机译：通过整合高通量基因组学数据，对卵巢癌中药物反应的基因表达的驾驶模式鉴定

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Xinguo Lu; Jibo Lu; Bo Liao; Keqin Li;
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年度 2017
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1. Driver pattern identification over the gene co-expression of drug response in ovarian cancer by integrating high throughput genomics data [J] . Xinguo Lu, Jibo Lu, Bo Liao, Scientific reports. . 2017,第1期

机译：通过整合高通量基因组学数据，鉴定卵巢癌药物反应基因共表达的驱动程序模式
2. Identifying candidate drivers of drug response in heterogeneous cancer by mining high throughput genomics data [J] . Sheida Nabavi BMC Genomics . 2016,第1期

机译：通过挖掘高通量基因组学数据来识别异质性癌症中药物反应的候选驱动因素
3. Identification of candidate cancer drivers by integrative Epi-DNA and Gene Expression (iEDGE) data analysis [J] . Amy Li, Bjoern Chapuy, Xaralabos Varelas, Scientific reports. . 2019,第1期

机译：通过整合EPI-DNA和基因表达（IEDGE）数据分析鉴定候选癌症司机
4. Identifying Candidate Driver Genes by Integrative Ovarian Cancer Genomics Data [C] . Xinguo Lu, Jibo Lu International Conference on Green Energy and Sustainable Development . 2017

机译：通过综合卵巢癌基因组学数据识别候选司机基因
5. Mining patterns in genomic and clinical cancer data to characterize novel driver genes. [D] . Melamed, Rachel D. 2015

机译：基因组和临床癌症数据中的挖掘模式可表征新型驱动基因。
6. Driver pattern identification over the gene co-expression of drug response in ovarian cancer by integrating high throughput genomics data [O] . Xinguo Lu, Jibo Lu, Bo Liao, -1

机译：通过整合高通量基因组学数据鉴定卵巢癌药物反应基因共表达的驱动程序模式
7. Identifying candidate drivers of drug response in heterogeneous cancer by mining high throughput genomics data [O] . Sheida Nabavi 2016

机译：通过挖掘高通量基因组学数据，确定异质性癌症中药物反应的候选驱动因素
8. Novel Approach to Identify Genes that Modulate Response of Human Ovarian Cancer Cells to Chemotherapeutic Agents Using High-Throughput RNA Interference [R] . Azorsa, D. 2008

机译：鉴定使用高通量RNa干扰调节对人卵巢癌细胞对化学治疗剂的反应的基因的新方法

Driver pattern identification over the gene co-expression of drug response in ovarian cancer by integrating high throughput genomics data

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