ArticleScientific reports2019
Using mechanistic models for the clinical interpretation of complex genomic variation.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed.
- Bottlenecks in advancing and applying multiomic data integration-common data resources as rate-limiting drivers-the high-impact use case of atherosclerotic cardiovascular disease.Briefings in bioinformatics · 2025Review
- drexml: A command line tool and Python package for drug repurposing.Computational and structural biotechnology journal · 2024Article
- SignalingProfiler 2.0 a network-based approach to bridge multi-omics data to phenotypic hallmarks.NPJ systems biology and applications · 2024Article
- The mechanistic functional landscape of retinitis pigmentosa: a machine learning-driven approach to therapeutic target discovery.Journal of translational medicine · 2024Article
- Immune and molecular landscape behind non-response to Mycophenolate Mofetil and Azathioprine in lupus nephritis therapy.Research square · 2024Article
- Associations between Host Genetic Variants and Subgingival Microbiota in Patients with the Metabolic Syndrome.International journal of molecular sciences · 2023Article
- Functional Profiling of Soft Tissue Sarcoma Using Mechanistic Models.International journal of molecular sciences · 2023Article
- Crosstalk between Metabolite Production and Signaling Activity in Breast Cancer.International journal of molecular sciences · 2023Article
- Population-enriched innate immune variants may identify candidate gene targets at the intersection of cancer and cardio-metabolic disease.Frontiers in endocrinology · 2023Review
- ESCCdb: A comprehensive database and key regulator exploring platform based on cross dataset comparisons for esophageal squamous cell carcinoma.Computational and structural biotechnology journal · 2023Article
- A Computational Platform Integrating a Mechanistic Model of Crohn's Disease for Predicting Temporal Progression of Mucosal Damage and Healing.Advances in therapy · 2022Article
- Discovering potential interactions between rare diseases and COVID-19 by combining mechanistic models of viral infection with statistical modeling.Human molecular genetics · 2022Article
- Mutational Characterization of Cutaneous Melanoma Supports Divergent Pathways Model for Melanoma Development.Cancers · 2021Article
- Web tools to fight pandemics: the COVID-19 experience.Briefings in bioinformatics · 2021Article
- A versatile workflow to integrate RNA-seq genomic and transcriptomic data into mechanistic models of signaling pathways.PLoS computational biology · 2021Article
- Mechanistic modeling of the SARS-CoV-2 disease map.BioData mining · 2021Article
- Genome-scale mechanistic modeling of signaling pathways made easy: A bioconductor/cytoscape/web server framework for the analysis of omic data.Computational and structural biotechnology journal · 2021Article
- Human Embryos, Induced Pluripotent Stem Cells, and Organoids: Models to Assess the Effects of Environmental Plastic Pollution.Frontiers in cell and developmental biology · 2021Review
- Article
- Genetic Modifiers and Rare Mendelian Disease.Genes · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The sustained generation of genomic data in the last decade has increased the knowledge on the causal mutations of a large number of diseases, especially for highly penetrant Mendelian diseases, typically caused by a unique or a few genes. However, the discovery of causal genes in complex diseases has been far less successful. Many complex diseases are actually a consequence of the failure of complex biological modules, composed by interrelated proteins, which can happen in many different ways, which conferring a multigenic nature to the condition that can hardly be attributed to one or a few genes. We present a mechanistic model, Hipathia, implemented in a web server that allows estimating the effect that mutations, or changes in the expression of genes, have over the whole system of human signaling and the corresponding functional consequences. We show several use cases where we demonstrate how different the ultimate impact of mutations with similar loss-of-function potential can be and how the potential pathological role of a damaged gene can be inferred within the context of a signaling network. The use of systems biology-based approaches, such as mechanistic models, allows estimating the potential impact of loss-of-function mutations occurring in proteins that are part of complex biological interaction networks, such as signaling pathways. This holistic approach provides an elegant alternative to gene-centric approaches that can open new avenues in the interpretation of the genomic variability in complex diseases.
Indexed as
Identifiers
What OpenQuestion holds
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.