ArticleGenome biology2025
A comparison of computational methods for expression forecasting.
Article in Genome biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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.
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.
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Who cites it
14 citing papers in PubMed.
- A systematic comparison of single-cell perturbation response prediction models.Science advances · 2026Article
- A transcription factor regulatory atlas for activity inference and perturbation prediction.Nucleic acids research · 2026Article
- Article
- TxPert: using multiple knowledge graphs for prediction of transcriptomic perturbation effects.Nature biotechnology · 2026Article
- Interpretation, extrapolation and perturbation of single cells.Nature reviews. Genetics · 2026Review
- Representation learning of single-cell RNA-seq data.RNA (New York, N.Y.) · 2026Review
- Stack: In-Context Learning of Single-Cell Biology.bioRxiv : the preprint server for biology · 2026Article
- Identification of Hub genes in melasma using integrated transcriptomic analysis.Bioinformation · 2026Article
- PerturbNet predicts single-cell responses to unseen chemical and genetic perturbations.Molecular systems biology · 2025Article
- Simple controls exceed best deep learning algorithms and reveal foundation model effectiveness for predicting genetic perturbations.Bioinformatics (Oxford, England) · 2025Article
- Article
- Toward automated and explainable high-throughput perturbation analysis in single cells.Patterns (New York, N.Y.) · 2025Article
- OneSC: a computational platform for recapitulating cell state transitions.Bioinformatics (Oxford, England) · 2024Article
- OneSC: A computational platform for recapitulating cell state transitions.bioRxiv : the preprint server for biology · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Diverse machine learning methods promise to forecast gene expression changes in response to novel genetic perturbations. However, these methods' accuracy is not well characterized. We created a benchmarking platform that combines a panel of 11 large-scale perturbation datasets with an expression forecasting software engine that encompasses or interfaces to a wide variety of methods. We used our platform to assess methods, parameters, and sources of auxiliary data, finding that it is uncommon for expression forecasting methods to outperform simple baselines. Our platform will serve as a resource to improve methods and to identify contexts in which expression forecasting can succeed.
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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.