The DOMINO web-server for active module identification analysis

Levi, Hagai; Rahmanian, Nima; Elkon, Ran; Shamir, Ron

doi:10.1093/bioinformatics/btac067

Cited by 5 publications

(4 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are also some web-based DMMMs, e.g. KeyPathwayMinerWeb ( List et al 2016 ), BiCoN ( Lazareva et al 2021a ), and the DOMINO web-server ( Levi et al 2022 ). However, unlike ROBUST-Web, none of these tools offers features to link the computed modules to drugs and diseases.…”

Section: Introductionmentioning

confidence: 99%

Online bias-aware disease module mining with ROBUST-Web

Sarkar

Lucchetta

Maier³

et al. 2023

Bioinformatics

View full text Add to dashboard Cite

Summary We present ROBUST-Web which implements our recently presented ROBUST disease module mining algorithm in a user-friendly web application. ROBUST-Web features seamless downstream disease module exploration via integrated gene set enrichment analysis, tissue expression annotation, and visualization of drug-protein and disease-gene links. Moreover, ROBUST-Web includes bias-aware edge costs for the underlying Steiner tree model as a new algorithmic feature, which allow to correct for study bias in protein-protein interaction networks and further improves the robustness of the computed modules. Availability and implementation Web application: https://robust-web.net. Source code of web application and Python package with new bias-aware edge costs: https://github.com/bionetslab/robust-web, https://github.com/bionetslab/robust_bias_aware. Supplementary information Supplementary data are available at Bioinformatics online.

show abstract

Section: Introductionmentioning

confidence: 99%

Online bias-aware disease module mining with ROBUST-Web

Sarkar

Lucchetta

Maier³

et al. 2023

Bioinformatics

View full text Add to dashboard Cite

show abstract

“…We used our recently developed DOMINO algorithm. The input of the analysis consists of a large protein-protein interaction (PPI) network and the set of DE genes and DOMINO searches the PPI of sub-networks of interacting proteins that are enriched for the DE genes (Levi et al, 2021(Levi et al, , 2022. Each such subnetwork (termed an "active module") represents a functional unit of interacting proteins.…”

Section: Resultsmentioning

confidence: 99%

“…The network analysis was conducted using DOMINO (http://domino.cs.tau. ac.il/) after mapping mouse genes to their human orthologs, only including genes with one-to-one mapping (Levi et al, 2021(Levi et al, , 2022.…”

Section: Rnaseq Normalization and Expression Analysismentioning

confidence: 99%

A cell type–specific approach to elucidate the role of miR-96 in inner ear hair cells

Gwilliam,

Sperber,

Perry

et al. 2024

Front. Audiol. Otol.

Self Cite

View full text Add to dashboard Cite

IntroductionMutations in microRNA-96 (miR-96), a microRNA expressed within the hair cells (HCs) of the inner ear, result in progressive hearing loss in both mouse models and humans. In this study, we present the first HC-specific RNA-sequencing (RNA-seq) dataset from newborn Mir96Dmdo heterozygous, homozygous mutant, and wildtype mice.MethodsBulk RNA-seq was performed on HCs of newborn Mir96Dmdo heterozygous, homozygous mutant, and wildtype mice. Differentially expressed gene analysis was conducted on Mir96Dmdo homozygous mutant HCs compared to wildtype littermate controls, followed by GO term and protein-protein interaction analysis on these differentially expressed genes.ResultsWe identify 215 upregulated and 428 downregulated genes in the HCs of the Mir96Dmdo homozygous mutant mice compared to their wildtype littermate controls. Many of the significantly downregulated genes in Mir96Dmdo homozygous mutant HCs have established roles in HC development and/or known roles in deafness including Myo15a, Myo7a, Ush1c, Gfi1, and Ptprq and have enrichment in gene ontology (GO) terms with biological functions such as sensory perception of sound. Interestingly, upregulated genes in Mir96Dmdo homozygous mutants, including possible miR-96 direct targets, show higher wildtype expression in supporting cells compared to HCs.ConclusionOur data further support a role for miR-96 in HC development, possibly as a repressor of supporting cell transcriptional programs in HCs. The HC-specific Mir96Dmdo RNA-seq data set generated from this manuscript are now publicly available in a dedicated profile in the gene expression analysis resource (gEAR-https://umgear.org/p?l=miR96).

show abstract

“…An active module is a connected subset of gene nodes in a biological interaction network relevant to the investigated condition. For the discovery of active modules that have high connectivity and contain a high number of target genes (considered as active genes), we use the DOMINO method [18] with the default parameters through its web server [24]. Following the active module identification, a pairwise overlap analysis is performed between all the identified active modules and all the rare disease pathways.…”

Section: Integrative Bioinformatics Approachesmentioning

confidence: 99%

ODAMNet: a Python package to identify molecular relationships between chemicals and rare diseases using overlap, active module and random walk approaches

Térézol

Baudot

Özışık

2023

Preprint

View full text Add to dashboard Cite

Environmental factors are external conditions that can affect the health of living organisms. For a number of rare genetic diseases, an interplay between genetic and environmental factors is known or suspected. However, the studies are limited by the scarcity of patients and the difficulties in gathering reliable exposure information. In order to aid in fostering research between environmental factors and rare diseases, we propose ODAMNet, a Python package to investigate the possible relationships between chemicals, which are a subset of environmental factors, and rare diseases. ODAMNet offers three different and complementary bioinformatics approaches for the exploration of relationships: overlap analysis, active module identification and random walk with restart. ODAMNet allows systematic analysis of chemical - rare disease relationships and generation of hypotheses for further investigation of effect mechanisms.

show abstract

The DOMINO web-server for active module identification analysis

Cited by 5 publications

References 22 publications

Online bias-aware disease module mining with ROBUST-Web

Online bias-aware disease module mining with ROBUST-Web

A cell type–specific approach to elucidate the role of miR-96 in inner ear hair cells

ODAMNet: a Python package to identify molecular relationships between chemicals and rare diseases using overlap, active module and random walk approaches

Contact Info

Product

Resources

About