ArticleNucleic acids research2015
Assessing the impact of mutations found in next generation sequencing data over human signaling pathways.
Article in Nucleic acids research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 19 citations in OpenAlex.
- Mechanistic modeling of the SARS-CoV-2 disease map.BioData mining · 2021Article
- Using mechanistic models for the clinical interpretation of complex genomic variation.Scientific reports · 2019Article
- A comparison of mechanistic signaling pathway activity analysis methods.Briefings in bioinformatics · 2019Review
- UnusualEndocrinology, diabetes & metabolism case reports · 2018Article
- High throughput estimation of functional cell activities reveals disease mechanisms and predicts relevant clinical outcomes.Oncotarget · 2017Article
- Annotating Mutational Effects on Proteins and Protein Interactions: Designing Novel and Revisiting Existing Protocols.Methods in molecular biology (Clifton, N.J.) · 2017Article
- Review
- Actionable pathways: interactive discovery of therapeutic targets using signaling pathway models.Nucleic acids research · 2016Article
- Chronic subordination stress selectively downregulates the insulin signaling pathway in liver and skeletal muscle but not in adipose tissue of male mice.Stress (Amsterdam, Netherlands) · 2016Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Modern sequencing technologies produce increasingly detailed data on genomic variation. However, conventional methods for relating either individual variants or mutated genes to phenotypes present known limitations given the complex, multigenic nature of many diseases or traits. Here we present PATHiVar, a web-based tool that integrates genomic variation data with gene expression tissue information. PATHiVar constitutes a new generation of genomic data analysis methods that allow studying variants found in next generation sequencing experiment in the context of signaling pathways. Simple Boolean models of pathways provide detailed descriptions of the impact of mutations in cell functionality so as, recurrences in functionality failures can easily be related to diseases, even if they are produced by mutations in different genes. Patterns of changes in signal transmission circuits, often unpredictable from individual genes mutated, correspond to patterns of affected functionalities that can be related to complex traits such as disease progression, drug response, etc. PATHiVar is available at: http://pathivar.babelomics.org.
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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.