ArticleCell systems2022
Sparse dictionary learning recovers pleiotropy from human cell fitness screens.
Article in Cell systems, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Mechanisms of transcription termination across the coding and noncoding loci of the genome.Nature reviews. Molecular cell biology · 2026Review
- Combinatorial prediction of therapeutic perturbations using causally inspired neural networks.Nature biomedical engineering · 2026Article
- Genotype-fitness mapping of adaptive mutants reveals shifting low-dimensional structure across divergent environments.PLoS biology · 2026Article
- A Co-essentiality Network of Cancer Driver Genes Better Prioritizes Anticancer Drugs.Genomics, proteomics & bioinformatics · 2025Article
- Deep Mutational Scanning of FDX1 Identifies Key Structural Determinants of Lipoylation and Cuproptosis.Nature communications · 2025Article
- Microbiome data integration via shared dictionary learning.Nature communications · 2025Article
- Discovery of chromatin-based determinants of azacytidine and decitabine anti-cancer activity.bioRxiv : the preprint server for biology · 2025Article
- Learning Universal Representations of Intermolecular Interactions with ATOMICA.bioRxiv : the preprint server for biology · 2025Article
- BaCoN (Balanced Correlation Network) improves prediction of gene buffering.Molecular systems biology · 2025Article
- The present and future of the Cancer Dependency Map.Nature reviews. Cancer · 2025Review
- Contextual AI models for single-cell protein biology.Nature methods · 2024Article
- Contextual AI models for context-specific prediction in biology.Nature methods · 2024Article
- Contextual AI models for single-cell protein biology.bioRxiv : the preprint server for biology · 2024Article
- On knowing a gene: A distributional hypothesis of gene function.Cell systems · 2024Review
- Predicting potential target genes in molecular biology experiments using machine learning and multifaceted data sources.iScience · 2024Article
- Evaluation of input data modality choices on functional gene embeddings.NAR genomics and bioinformatics · 2023Article
- Dimensionality reduction methods for extracting functional networks from large-scale CRISPR screens.Molecular systems biology · 2023Article
- Inferring sparse structure in genotype-phenotype maps.Genetics · 2023Article
- Context-defined cancer co-dependency mapping identifies a functional interplay between PRC2 and MLL-MEN1 complex in lymphoma.Nature communications · 2023Article
- A multi-scale map of protein assemblies in the DNA damage response.Cell systems · 2023Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
In high-throughput functional genomic screens, each gene product is commonly assumed to exhibit a singular biological function within a defined protein complex or pathway. In practice, a single gene perturbation may induce multiple cascading functional outcomes, a genetic principle known as pleiotropy. Here, we model pleiotropy in fitness screen collections by representing each gene perturbation as the sum of multiple perturbations of biological functions, each harboring independent fitness effects inferred empirically from the data. Our approach (Webster) recovered pleiotropic functions for DNA damage proteins from genotoxic fitness screens, untangled distinct signaling pathways upstream of shared effector proteins from cancer cell fitness screens, and predicted the stoichiometry of an unknown protein complex subunit from fitness data alone. Modeling compound sensitivity profiles in terms of genetic functions recovered compound mechanisms of action. Our approach establishes a sparse approximation mechanism for unraveling complex genetic architectures underlying high-dimensional gene perturbation readouts.
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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 Socratic graph.