Suppr超能文献

ITTACA:一个用于整合肿瘤转录组阵列和临床数据分析的新数据库。

ITTACA: a new database for integrated tumor transcriptome array and clinical data analysis.

作者信息

Elfilali Adil, Lair Séverine, Verbeke Catia, La Rosa Philippe, Radvanyi François, Barillot Emmanuel

机构信息

Institut Curie, Service Bioinformatique, 26 rue d'Ulm, Paris, 75248 cedex 05, France.

出版信息

Nucleic Acids Res. 2006 Jan 1;34(Database issue):D613-6. doi: 10.1093/nar/gkj022.

Abstract

Transcriptome microarrays have become one of the tools of choice for investigating the genes involved in tumorigenesis and tumor progression, as well as finding new biomarkers and gene expression signatures for the diagnosis and prognosis of cancer. Here, we describe a new database for Integrated Tumor Transcriptome Array and Clinical data Analysis (ITTACA). ITTACA centralizes public datasets containing both gene expression and clinical data. ITTACA currently focuses on the types of cancer that are of particular interest to research teams at Institut Curie: breast carcinoma, bladder carcinoma and uveal melanoma. A web interface allows users to carry out different class comparison analyses, including the comparison of expression distribution profiles, tests for differential expression and patient survival analyses. ITTACA is complementary to other databases, such as GEO and SMD, because it offers a better integration of clinical data and different functionalities. It also offers more options for class comparison analyses when compared with similar projects such as Oncomine. For example, users can define their own patient groups according to clinical data or gene expression levels. This added flexibility and the user-friendly web interface makes ITTACA especially useful for comparing personal results with the results in the existing literature. ITTACA is accessible online at http://bioinfo.curie.fr/ittaca.

摘要

转录组微阵列已成为研究肿瘤发生和肿瘤进展相关基因,以及寻找癌症诊断和预后新生物标志物及基因表达特征的首选工具之一。在此,我们描述了一个用于综合肿瘤转录组阵列和临床数据分析(ITTACA)的新数据库。ITTACA集中了包含基因表达和临床数据的公共数据集。ITTACA目前专注于居里研究所研究团队特别感兴趣的癌症类型:乳腺癌、膀胱癌和葡萄膜黑色素瘤。一个网络界面允许用户进行不同的类别比较分析,包括表达分布谱比较、差异表达测试和患者生存分析。ITTACA与其他数据库(如GEO和SMD)互补,因为它能更好地整合临床数据和不同功能。与Oncomine等类似项目相比,它还为类别比较分析提供了更多选项。例如,用户可以根据临床数据或基因表达水平定义自己的患者组。这种增加的灵活性和用户友好的网络界面使ITTACA对于将个人结果与现有文献中的结果进行比较特别有用。可通过http://bioinfo.curie.fr/ittaca在线访问ITTACA。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eff3/1347385/3583f8601b27/gkj022f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验