ArticleBioinformatics (Oxford, England)2012
Expression2Kinases: mRNA profiling linked to multiple upstream regulatory layers.
Article in Bioinformatics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 110 papers, 4 of them syntheses that pooled it.
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Who cites it
110 citing papers in PubMed, 4 syntheses or guidelines pooled it, 186 citations in OpenAlex.
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- Comprehensive Gene expression meta-analysis and integrated bioinformatic approaches reveal shared signatures between thrombosis and myeloproliferative disorders.Scientific reports · 2016Pooled it
- Role of innate immunity-triggered pathways in the pathogenesis of Sickle Cell Disease: a meta-analysis of gene expression studies.Scientific reports · 2015Pooled it
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- Benchmarking of protein interaction databases for integration with manually reconstructed signalling network models.The Journal of physiology · 2024Article
- Multiomics2Targets identifies targets from cancer cohorts profiled with transcriptomics, proteomics, and phosphoproteomics.Cell reports methods · 2024Article
- Proteomic Changes Induced by the Immunosuppressant Everolimus in Human Podocytes.International journal of molecular sciences · 2024Article
- In silico exploration of anti-prostate cancer compounds from differential expressed genes.BMC urology · 2024Article
50 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
motivationGenome-wide mRNA profiling provides a snapshot of the global state of cells under different conditions. However, mRNA levels do not provide direct understanding of upstream regulatory mechanisms. Here, we present a new approach called Expression2Kinases (X2K) to identify upstream regulators likely responsible for observed patterns in genome-wide gene expression. By integrating chromatin immuno-precipitation (ChIP)-seq/chip and position weight matrices (PWMs) data, protein-protein interactions and kinase-substrate phosphorylation reactions, we can better identify regulatory mechanisms upstream of genome-wide differences in gene expression. We validated X2K by applying it to recover drug targets of food and drug administration (FDA)-approved drugs from drug perturbations followed by mRNA expression profiling; to map the regulatory landscape of 44 stem cells and their differentiating progeny; to profile upstream regulatory mechanisms of 327 breast cancer tumors; and to detect pathways from profiled hepatic stellate cells and hippocampal neurons. The X2K approach can advance our understanding of cell signaling and unravel drugs mechanisms of action. AVAILABILITY: The software and source code are freely available at: http://www.maayanlab.net/X2K. CONTACT: avi.maayan@mssm.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.