ReviewmSystems2026
The iModulon framework: how x-AI reveals microbial regulatory logic.
Review in mSystems, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
The accelerating deposition of RNAseq data over the past decade has motivated the development of advanced transcriptomic data analytics that can operate on a large number of samples. One successful approach is to apply independent component analysis (ICA) to large prokaryotic transcriptomic compendia to decompose them into independently modulated gene sets, called iModulons. Here, we review the data science principles underlying ICA-based transcriptome decomposition, computational workflows that support its routine application, and iModulonDB infrastructure that hosts and disseminates the resulting decompositions. We present iModulonDB 3.0 that contains 53 species and 71 ICA decompositions across 33,062 RNA-seq samples, with several well-sampled species (e.g.,
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What Socratic 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 Socratic graph.