详情页 - 四川省肿瘤医院知识库

当前位置：首页 > 详情页

Translational Bioinformatics for Cholangiocarcinoma: Opportunities and Challenges.

文献详情

资源类型：

Pubmed体系：

作者：

机构： [1]Center for Systems Biology, Soochow University, Suzhou 215006, China. [2]The Affiliated Yixing Hospital of Jiangsu University, Yixing, 214200, China. [3]Guizhou University School of Medicine, Guiyang, 550025, China. [4]Institute for Systems Genetics, West China Hospital, Sichuan University, Chengdu, 610041, China.

出处：

DOI：

关键词： cholangiocarcinoma bioinformatics model precision diagnosis and prognosis biomarkers discovery

摘要：

Translational bioinformatics is becoming a driven force and a new scientific paradigm for cancer research in the era of big data. To promote the cross-disciplinary communication and research, we take cholangiocarcinoma as an example to review the present status and the future perspectives of the bioinformatics models applied in cancer study. We first summarize the present application of computational methods to the study of cholangiocarcinoma ranged from pattern recognition of biological data, knowledge based data annotation to systems biological level modeling and clinical translation. Then the future opportunities and challenges about database or knowledge base building, novel model developing and molecular mechanism exploring as well as the intelligent decision supporting system construction for the precision diagnosis, prognosis and treatment of cholangiocarcinoma are discussed.

基金：

语种：

PubmedID：

中科院(CAS)分区：

出版当年[2018]版：

大类 | 2 区生物

小类 | 3 区生化与分子生物学

最新[2023]版：

大类 | 2 区

生物学

小类 | 2 区生化与分子生物学

第一作者：

第一作者机构： [1]Center for Systems Biology, Soochow University, Suzhou 215006, China.

通讯作者：

通讯机构： [1]Center for Systems Biology, Soochow University, Suzhou 215006, China. [3]Guizhou University School of Medicine, Guiyang, 550025, China. [4]Institute for Systems Genetics, West China Hospital, Sichuan University, Chengdu, 610041, China.

推荐引用方式(GB/T 7714)：

APA：

MLA：

相关文献

[1]MiRNA-BD: an evidence-based bioinformatics model and software tool for microRNA biomarker discovery. [2]Bioinformatics & Machine Learning for Prognostic Model of LUSC by Identifying Programmed Cell Death Genes [3]Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model. [4]Case Report: Primary lymphoepithelioma-like intrahepatic cholangiocarcinoma [5]Downregulation of MCM8 expression restrains the malignant progression of cholangiocarcinoma [6]Network vulnerability-based and knowledge-guided identification of microRNA biomarkers indicating platinum resistance in high-grade serous ovarian cancer. [7]Vemurafenib inhibits immune escape biomarker BCL2A1 by targeting PI3K/AKT signaling pathway to suppress breast cancer [8]Proteogenomic characterization identifies clinically relevant subgroups of intrahepatic cholangiocarcinoma. [9]Imaging features predict prognosis of patients with combined hepatocellular-cholangiocarcinoma [10]The clinical value of regional lymphadenectomy for intrahepatic cholangiocarcinoma.