miTALOS v2: Analyzing Tissue Specific microRNA Function

Preusse, Martin; Theis, Fabian J.; Mueller, Nikola S.

doi:10.1371/journal.pone.0151771

Cited by 70 publications

(59 citation statements)

References 57 publications

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“…MiRGator combines three miRNA target prediction programmes and focuses on the expression analysis and GSEA to facilitate functional annotation of miRNAs (62). MiTALOS accounts for miRNA tissue specificity by introducing a novel pathway analysis methodology (63). …”

Section: Resultsmentioning

confidence: 99%

IRNdb: the database of immunologically relevant non-coding RNAs

Denisenko

Tamgue

et al. 2016

Database

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MicroRNAs (miRNAs), long non-coding RNAs (lncRNAs) and other functional non-coding RNAs (ncRNAs) have emerged as pivotal regulators involved in multiple biological processes. Recently, ncRNA control of gene expression has been identified as a critical regulatory mechanism in the immune system. Despite the great efforts made to discover and characterize ncRNAs, the functional role for most remains unknown. To facilitate discoveries in ncRNA regulation of immune system-related processes, we developed the database of immunologically relevant ncRNAs and target genes (IRNdb). We integrated mouse data on predicted and experimentally supported ncRNA-target interactions, ncRNA and gene annotations, biological pathways and processes and experimental data in a uniform format with a user-friendly web interface. The current version of IRNdb documents 12 930 experimentally supported miRNA-target interactions between 724 miRNAs and 2427 immune-related mouse targets. In addition, we recorded 22 453 lncRNA-immune target and 377 PIWI-interacting RNA-immune target interactions. IRNdb is a comprehensive searchable data repository which will be of help in studying the role of ncRNAs in the immune system.Database URL: http://irndb.org

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Section: Resultsmentioning

confidence: 99%

IRNdb: the database of immunologically relevant non-coding RNAs

Denisenko

Tamgue

et al. 2016

Database

View full text Add to dashboard Cite

show abstract

“…MiRGator combines three miRNA target prediction programs and focuses on the expression analysis and gene set enrichment analysis to facilitate functional annotation of miRNAs (62). MiTALOS accounts for miRNA tissue specificity by introducing a novel pathway analysis methodology (63).…”

Section: Resultsmentioning

confidence: 99%

IRNdb: The database of immunologically relevant non-coding RNAs

Denisenko

Tamgue

et al. 2016

Preprint

View full text Add to dashboard Cite

MicroRNAs (miRNAs), long non-coding RNAs (lncRNAs) and other functional non-coding RNAs (ncRNAs) have emerged as pivotal regulators involved in multiple biological processes. Recently, ncRNA control of gene expression has been identified as a critical regulatory mechanism in the immune system. Despite the great efforts made to discover and characterize ncRNAs, the functional role for most remains unknown. To facilitate discoveries in ncRNA regulation of immune system-related processes, we developed the database of immunologically relevant ncRNAs and target genes (IRNdb). We integrated mouse data on predicted and experimentally supported ncRNA-target interactions, ncRNA and gene annotations, biological pathways and processes and experimental data in a uniform format with a user-friendly web interface. The current version of IRNdb documents 12 930 experimentally supported miRNA-target interactions between 724 miRNAs and 2427 immune-related mouse targets. In addition, we recorded 22 453 lncRNA-immune target and 377 PIWIinteracting RNA-immune target interactions. IRNdb is a comprehensive searchable data repository which will be of help in studying the role of ncRNAs in the immune system.Database URL: http://irndb.org V C The Author(s)

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“…Differentially expressed miRNAs were analyzed with mirPATH (v3.0) [12], miTALOS (v2) [13], and miR-Net (v2.0) [14] for target gene pathway enrichment. These multiple tools were used for their application of multiple pathway databases (e.g.…”

Section: Functional and Target Analysismentioning

confidence: 99%

Integrative analysis of breast cancer profiles in TCGA by TNBC subgrouping reveals novel microRNA-specific clusters, including miR-17-92a, distinguishing basal-like 1 and basal-like 2 TNBC subtypes

et al. 2020

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Background: The term triple-negative breast cancer (TNBC) is used to describe breast cancers without expression of estrogen receptor, progesterone receptor or HER2 amplification. To advance targeted treatment options for TNBC, it is critical that the subtypes within this classification be described in regard to their characteristic biology and gene expression. The Cancer Genome Atlas (TCGA) dataset provides not only clinical and mRNA expression data but also expression data for microRNAs.Results: In this study, we applied the Lehmann classifier to TCGA-derived TNBC cases which also contained microRNA expression data and derived subtype-specific microRNA expression patterns. Subsequent analyses integrated known and predicted microRNA-mRNA regulatory nodes as well as patient survival data to identify key networks. Notably, basal-like 1 (BL1) TNBCs were distinguished from basal-like 2 TNBCs through up-regulation of members of the miR-17-92 cluster of microRNAs and suppression of several known miR-17-92 targets including inositol polyphosphate 4-phosphatase type II, INPP4B.Conclusions: These data demonstrate TNBC subtype-specific microRNA and target mRNA expression which may be applied to future biomarker and therapeutic development studies.

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miTALOS v2: Analyzing Tissue Specific microRNA Function

Cited by 70 publications

References 57 publications

IRNdb: the database of immunologically relevant non-coding RNAs

IRNdb: the database of immunologically relevant non-coding RNAs

IRNdb: The database of immunologically relevant non-coding RNAs

Integrative analysis of breast cancer profiles in TCGA by TNBC subgrouping reveals novel microRNA-specific clusters, including miR-17-92a, distinguishing basal-like 1 and basal-like 2 TNBC subtypes

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