Evidence map›Paper›PMID 36016717›Full record

ReviewComputational and structural biotechnology journal2022

Using genome-wide expression compendia to study microorganisms.

Alexandra J Lee, Taylor Reiter, Georgia Doing, Julia Oh, Deborah A Hogan, Casey S Greene

Abstract readReview
In one paragraph

Review in Computational and structural biotechnology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Alexandra J LeeGenomics and Computational Biology Graduate Program, University of Pennsylvania, Philadelphia, PA, USA.
Taylor ReiterDepartment of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Denver, CO, USA.
Georgia DoingThe Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
Julia OhThe Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
Deborah A HoganDepartment of Microbiology and Immunology, Geisel School of Medicine, Dartmouth, Hanover, NH, USA.
Casey S GreeneDepartment of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Denver, CO, USA.

Funding

Technology Development Project - Increasing the complexity of ex vivo human airway models for studying immune response to viral infectionU19AI142733 · NIAID · JACKSON LABORATORY · PI Anna Karolina Palucka · 2019 to 2026
$23.1M
Topological Mapping of Immune, Microbiota, Metabolomic and Clinical Phenotypes to Reveal ME/CFS Disease Mechanisms - Clinical Research ProjectU54NS105539 · NINDS · JACKSON LABORATORY · PI VERNON, SUZANNE D · 2017 to 2022
$10.6M
Metagenomes to Therapeutics: Defining the Rules for Engineering the Skin MicrobiomeDP2GM126893 · NIGMS · JACKSON LABORATORY · PI OH, JULIA · 2017 to 2017
$2.8M
Molecular Mechanisms of Staphylococcus Epidermidis Strain DiversityR01AR078634 · NIAMS · JACKSON LABORATORY · PI OH, JULIA · 2021 to 2025
$2.5M
NIAID NIH HHS U19 AI142733NIAMS NIH HHS R01 AR078634NIGMS NIH HHS DP2 GM126893
6 · The paper itself

Abstract

A gene expression compendium is a heterogeneous collection of gene expression experiments assembled from data collected for diverse purposes. The widely varied experimental conditions and genetic backgrounds across samples creates a tremendous opportunity for gaining a systems level understanding of the transcriptional responses that influence phenotypes. Variety in experimental design is particularly important for studying microbes, where the transcriptional responses integrate many signals and demonstrate plasticity across strains including response to what nutrients are available and what microbes are present. Advances in high-throughput measurement technology have made it feasible to construct compendia for many microbes. In this review we discuss how these compendia are constructed and analyzed to reveal transcriptional patterns.

Indexed as

CompendiaMachine learningMicrobiologyTranscriptomics

Identifiers

PMID36016717
PMCPMC9396250

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.