ArticleMolecular systems biology2023
Predicting molecular mechanisms of hereditary diseases by using their tissue-selective manifestation.
Article in Molecular systems biology, 2023. 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
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
9 citing papers in PubMed.
- Network-based framework for studying etiology and phenotypic diversity in primary ciliopathies.Genome biology · 2026Article
- UNITe: exploiting conserved links between oncogenesis and homeostasis to identify novel cancer drivers.Frontiers in oncology · 2026Article
- Human clearance systems have a layered architecture across tissues and cell types that supports varied proteome compositions.Autophagy · 2026Article
- Network-based anomaly detection algorithm reveals proteins with major roles in human tissues.GigaScience · 2025Article
- Tissue-aware interpretation of genetic variants advances the etiology of rare diseases.Molecular systems biology · 2024Article
- Machine-learning analysis reveals an important role for negative selection in shaping cancer aneuploidy landscapes.Genome biology · 2024Article
- SPIDER: constructing cell-type-specific protein-protein interaction networks.Bioinformatics advances · 2024Article
- Predicting molecular mechanisms of hereditary diseases by using their tissue-selective manifestation.Molecular systems biology · 2023Article
- ProAct: quantifying the differential activity of biological processes in tissues, cells, and user-defined contexts.Nucleic acids research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
Abstract
How do aberrations in widely expressed genes lead to tissue-selective hereditary diseases? Previous attempts to answer this question were limited to testing a few candidate mechanisms. To answer this question at a larger scale, we developed "Tissue Risk Assessment of Causality by Expression" (TRACE), a machine learning approach to predict genes that underlie tissue-selective diseases and selectivity-related features. TRACE utilized 4,744 biologically interpretable tissue-specific gene features that were inferred from heterogeneous omics datasets. Application of TRACE to 1,031 disease genes uncovered known and novel selectivity-related features, the most common of which was previously overlooked. Next, we created a catalog of tissue-associated risks for 18,927 protein-coding genes (https://netbio.bgu.ac.il/trace/). As proof-of-concept, we prioritized candidate disease genes identified in 48 rare-disease patients. TRACE ranked the verified disease gene among the patient's candidate genes significantly better than gene prioritization methods that rank by gene constraint or tissue expression. Thus, tissue selectivity combined with machine learning enhances genetic and clinical understanding of hereditary 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.