@article{053b2a2ceb5349658018ea786ae4e06f,
title = "ADEPTUS: A discovery tool for disease prediction, enrichment and network analysis based on profiles from many diseases",
abstract = "Motivation Large-scale publicly available genomic data on many disease phenotypes could improve our understanding of the molecular basis of disease. Tools that undertake this challenge by jointly analyzing multiple phenotypes are needed. Results ADEPTUS is a web-tool that enables various functional genomics analyses based on a high-quality curated database spanning >38, 000 gene expression profiles and >100 diseases. It offers four types of analysis. (i) For a gene list provided by the user it computes disease ontology (DO), pathway, and gene ontology (GO) enrichment and displays the genes as a network. (ii) For a given disease, it enables exploration of drug repurposing by creating a gene network summarizing the genomic events in it. (iii) For a gene of interest, it generates a report summarizing its behavior across several studies. (iv) It can predict the tissue of origin and the disease of a sample based on its gene expression or its somatic mutation profile. Such analyses open novel ways to understand new datasets and to predict primary site of cancer.",
author = "David Amar and Amir Vizel and Carmit Levy and Ron Shamir",
note = "Publisher Copyright: {\textcopyright} The Author(s) 2018. Published by Oxford University Press.",
year = "2018",
month = jun,
day = "1",
doi = "10.1093/bioinformatics/bty027",
language = "אנגלית",
volume = "34",
pages = "1959--1961",
journal = "Bioinformatics",
issn = "1367-4803",
publisher = "Oxford University Press",
number = "11",
}