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Resource:Integrated Tumor Transcriptome Array and Clinical data Analysis

Name: Resource:Integrated Tumor Transcriptome Array and Clinical data Analysis
Description:

ITTACA is a database created for Integrated Tumor Transcriptome Array and Clinical data Analysis. ITTACA centralizes public datasets containing both gene expression and clinical data and currently focuses on the types of cancer that are of particular interest to the Institut Curie: breast carcinoma, bladder carcinoma, and uveal melanoma. ITTACA is developed by the Institut Curie Bioinformatics group and the Molecular Oncology group of UMR144 CNRS/Institut Curie.
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 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.
A web interface allows users to carry out different class comparison analyses, including comparison of expression distribution profiles, tests for differential expression, patient survival analyses, and users can define their own patient groups according to clinical data or gene expression levels.
The different functionalities implemented in ITTACA are:
- To test if one or more gene, of your choice, is differentially expressed between two groups of samples exhibiting distinct phenotypes (Student and Wilcoxon tests).
- The detection of genes differentially expressed (Significance Analysis of Microarrays) between two groups of samples.
- The creation of histograms which represent the expression level according to a clinical parameter for each sample.

- The computation of Kaplan Meier survival curves for each group.
Other Name(s): ITTACA
Parent Organization: Institut Curie
Resource Type(s): web accessible database
Keywords: expression, gene, analysis, array, bioinformatics, bladder, breast, cancer, carcinoma, clinical, integrated, melanoma, microarray, molecular, oncology, patient, phenotype, survival, transcriptome, tumor, uveal
Resource: Resource
URL: http://bioinfo-out.curie.fr/ittaca/
Id: nif-0000-21227
Link to OWL / RDF: Download this content as OWL/RDF

Curation status: Curated

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Facts about Resource:Integrated Tumor Transcriptome Array and Clinical data AnalysisRDF feed
CurationStatusuncurated  +
DefiningCitationhttp://bioinfo-out.curie.fr/ittaca/  +
Definition

ITTACA is a database created for I
ITTACA is a database created for Integrated Tumor Transcriptome Array and Clinical data Analysis. ITTACA centralizes public datasets containing both gene expression and clinical data and currently focuses on the types of cancer that are of particular interest to the Institut Curie: breast carcinoma, bladder carcinoma, and uveal melanoma. ITTACA is developed by the Institut Curie Bioinformatics group and the Molecular Oncology group of UMR144 CNRS/Institut Curie.
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 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.
A web interface allows users to carry out different class comparison analyses, including comparison of expression distribution profiles, tests for differential expression, patient survival analyses, and users can define their own patient groups according to clinical data or gene expression levels.
The different functionalities implemented in ITTACA are:
- To test if one or more gene, of your choice, is differentially expressed between two groups of samples exhibiting distinct phenotypes (Student and Wilcoxon tests).
- The detection of genes differentially expressed (Significance Analysis of Microarrays) between two groups of samples.
- The creation of histograms which represent the expression level according to a clinical parameter for each sample.

- The computation of Kaplan Meier survival curves for each group.
eier survival curves for each group.
Has default formThis property is a special property in this wiki.Resource  +
Has roleWeb accessible database  +
Idnif-0000-21227  +
Is part ofInstitut Curie  +
KeywordsExpression  +, Gene  +, Analysis  +, Array  +, Bioinformatics  +, Bladder  +, Breast  +, Cancer  +, Carcinoma  +, Clinical  +, Integrated  +, Melanoma  +, Microarray  +, Molecular  +, Oncology  +, Patient  +, Phenotype  +, Survival  +, Transcriptome  +, Tumor  +, and Uveal  +
LabelResource:Integrated Tumor Transcriptome Array and Clinical data Analysis  +
ModifiedDate13 October 2010  +
SuperCategoryResource  +
SynonymITTACA  +