Article

Learning perturbation-inducible cell states of novel compounds from observability analysis of transcriptome dynamics

2022-05-28

Abstract excerpt

A major challenge in biotechnology and biomanufacturing is the identification of a set of biomarkers for perturbations and metabolites of interest. Here, we develop a data-driven, transcriptome-wide approach to rank perturbation-inducible genes from time-series RNA sequencing data for the discovery of analyte-responsive promoters. This provides a set of biomarkers that act as a proxy for the transcriptional state...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: a8f9dabd-a3b4-56f8-82cf-4b0b95f2ba89
DOI: 10.1101/2022.05.27.493781

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Learning perturbation-inducible cell states of novel compounds from observability analysis of transcriptome dynamicsDOI 10.1101/2022.05.27.493781Read

Learning Perturbation-specific Cell Representations for Prediction of Transcriptional Response across Cellular ContextsSemantic proximity Read

Microbial forensics: predicting phenotypic characteristics and environmental conditions from large-scale gene expression profiles.Semantic proximity Read

High-throughput transcriptomics and benchmark concentration modeling for potency ranking of per- and polyfluoroalkyl substances (PFAS) in exposed human liver cell spheroidsSemantic proximity Read

Perturbation-Specific Transcriptional Mapping for unbiased target elucidation of antibioticsSemantic proximity Read

Mining Microbial Transcriptomes to Engineer Cell-Based Bacterial Biosensors in Gut-Resident BacteroidaceaeSemantic proximity Read

Identification of alterations in the Jacobian of biochemical reaction networks from steady state covariance data at two conditions.Semantic proximity Read

Knowledge-Driven Approaches to Create the MTox700+ Metabolite Panel for Predicting Toxicity.Semantic proximity Read

ARACRA: Automated RNA-seq Analysis for Chemical Risk AssessmentSemantic proximity Read

Deciphering per- and polyfluoroalkyl substances mode of action: comparative gene expression analysis in human liver spheroidsSemantic proximity Read

Integrative computational toxicology reveals PFOS and PFHxS associated inflammatory keratinocyte niches in psoriasis through exposure transcriptomics, single-cell spatial mapping and token-aware virtual perturbationSemantic proximity Read

Probe-based bacterial single-cell RNA sequencing predicts toxin regulationSemantic proximity Read

Transcriptome response to pollutants and insecticides in the dengue vector Aedes aegypti using next-generation sequencing technologySemantic proximity Read