Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA96589 | ENA |
REPOSITORIES: ENA
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Project description:The identification of gene regulatory modules is an important yet challenging problem in computational biology. While many computational methods have been proposed to identify regulatory modules, their initial success is largely compromised by a high rate of false positives, especially when applied to human cancer studies. New strategies are needed for reliable regulatory module identification. We present a new approach, namely multi-level support vector regression (ml-SVR), to systematically identify conditionspecific regulatory modules. The approach is built upon a multi-level analysis strategy designed for suppressing false positive predictions. With this strategy, a regulatory module becomes ever more significant as more relevant gene sets are formed at finer levels. At each level, a two-stage support vector regression (SVR) method is utilized to help reduce false positive predictions by integrating binding motif information and gene expression data; a significant analysis procedure is followed to assess the significance of each regulatory module. We applied our method to breast cancer cell line data to identify condition-specific regulatory modules associated with estrogen treatment. Experimental results show that our method can identify biologically meaningful regulatory modules related to estrogen signaling and action in breast cancer. Three independent total RNA samples were extracted for each cell line (MCF-7 and MCF-7-stripped) and the samples were arrayed using Affymetrix GeneChip HG-U133A. MCF-7-stripped denotes estrogen-deprived MCF-7 human breast cancer cells, which were grown in the absence of estrogen for 96 hours. We analyzed the enriched motifs and their targets for the genes significantly down-regulated in MCF-7-stripped cells as compared to MCF-7 cells.
2010-03-23 | E-GEOD-20700 | biostudies-arrayexpress
Project description:Our computational approach identified E2F1 as a potential collaborator of EZH2 in androgen-independent prostate cancer. This experiment is to designed to validate the crosstalking of E2F1 and EZH2 pathways. We showed that majority of the EZH2-induced genes in androgen-independent prostate tumor cells are in downstream of E2F1, providing insight into the EZH2-E2F1 collaborative regulatory pathway.
2016-01-22 | GSE56331 | GEO
Project description:The identification of gene regulatory modules is an important yet challenging problem in computational biology. While many computational methods have been proposed to identify regulatory modules, their initial success is largely compromised by a high rate of false positives, especially when applied to human cancer studies. New strategies are needed for reliable regulatory module identification. We present a new approach, namely multi-level support vector regression (ml-SVR), to systematically identify conditionspecific regulatory modules. The approach is built upon a multi-level analysis strategy designed for suppressing false positive predictions. With this strategy, a regulatory module becomes ever more significant as more relevant gene sets are formed at finer levels. At each level, a two-stage support vector regression (SVR) method is utilized to help reduce false positive predictions by integrating binding motif information and gene expression data; a significant analysis procedure is followed to assess the significance of each regulatory module. We applied our method to breast cancer cell line data to identify condition-specific regulatory modules associated with estrogen treatment. Experimental results show that our method can identify biologically meaningful regulatory modules related to estrogen signaling and action in breast cancer.
2010-03-10 | GSE20700 | GEO
Project description:We performed genome-wide location analysis for Foxa2 to identify its targets in the adult mouse liver. Chromatin isolated from the liver of five adult mice was cross-linked, sheared and immunoprecipitated with a Foxa2-specific antibody. The resulting material, as well as material that was not immunoprecipitated, was uncross-linked, amplified, labeled and hybridized to the Mouse Promoter Chip BCBC-5A. Statistical analysis resulted in a set of 107 genes that are bound by Foxa2. Using computational analyses, we showed that Foxa2 containing cis-regulatory modules are dependent on the strength of the Foxa2 consensus site present.
2008-07-04 | E-MTAB-32 | biostudies-arrayexpress
Project description:The abstract of the manuscript titled "Identification of co-regulated genes and cis-regulatory modules in Drosophila contractile cardiomyocytes" is given below: "Understanding how sets of genes are co-regulated to generate cell diversity during metazoan development is a major challenge. This requires the identification of tightly co-expressed genes in a given developmental process, of the responsible cis-regulatory modules, and of the combination of trans-acting transcription factors. We chose the Drosophila cardiac tube to address this issue. The cardiac tube is composed of a rostral aorta and a caudal heart, with distinct morphologies and functions and its development is controlled by conserved transcription factors. Our goal was to identify heart specific expressed genes and to use a combination of genetic and bioinformatic tools to identify and characterize their heart cis-regulatory modules (CRMs). By combined candidate gene approach and microarray experiments, we found 15 different genes that are specifically co-expressed in the contractile cardiomyocytes of the heart. Potential heart-specific CRMs were retrieved from evolutionary conserved non-coding sequences that were ranked according to an integrated score based on combinations of conserved occurrences of potential binding sites for transcription factors known to be expressed in the cardiovascular system, namely Abd-A, Tin, GATA, Mef2, Hand, and T-box factors. Candidate CRMs were then tested in vivo by generating nGFP reporter construct transgenic flies, allowing the identification of three heart enhancers precisely reproducing endogenous gene expression in the heart. We identified 15 genes that are tightly co-regulated in the contractile cardiomyocytes of the heart and for three of them found the responsible enhancer through computational predictions. A computational post-analysis suggests that different combinations of heart transcription factors may regulate these enhancers and permits to further refine the in silico identification of heart-specific CRMs."
2008-10-29 | GSE12539 | GEO
Project description:We captured chromatin accessibility branching using ATAC-seq in isolated NR and RPE populations in zebrafish. We identify differentially active cis-regulatory modules and classify them as activating or repressing elements.
2021-05-06 | GSE150189 | GEO
Project description:Genotyping 323 Europeans in order to perform cis-eQTL analysis in 9 tissue cell types. Identification of regulatory modules across genes and tissues on the basis of correlated SNPs in expression associated patterns. Integration of cis-eQTLs regulatory modules with known 200 IBD loci.
2018-04-28 | E-MTAB-6666 | biostudies-arrayexpress
Project description:The goal of this study is to identify co-expressed genes downstream of Atonal and Senseless. These gene lists are used as candidate target genes (technically: as foreground sets) in computational predictions of cis-regulatory elements using the cisTargetX method (http://med.kuleuven.be/cme-mg/lng/cisTargetX). Together, the gene expression results and cis-regulatory predictions, yield a gene regulatory network underlying the early events in retinal differentiation. Predicted cis-regulatory interactions have been validated extensively in vivo using enhancer reporter assays and genetic perturbations.
2010-06-28 | GSE16713 | GEO
Project description:Transcriptome in 6 immune cell types and 3 colonic biopsis from 323 individuals in order to perform cis-eQTL analysis. Identification of regulatory modules across genes and tissues on the basis of correlated SNPs in expression associated patterns (EAPs). Integration of cis-eQTLs regulatory modules with known 200 IBD loci.
2018-04-28 | E-MTAB-6667 | biostudies-arrayexpress