Evidence map›Paper›PMID 38162633›Full record

ArticleACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine2023

Dual ICA to extract interacting sets of genes and conditions from transcriptomic data.

Sanjeevani Choudhery, Thomas R Ioerger

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine, 2023. 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, top 87% of its field
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, 0 citations in OpenAlex.

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

2 authors at 1 institution in 1 country.

Sanjeevani ChoudheryDepartment of Computer Science and Computer Engineering, Texas A&M University, College Station, TX, 77840.
Thomas R IoergerDepartment of Computer Science and Computer Engineering, Texas A&M University, College Station, TX, 77840.
Texas A&M University · US

Funding

Surviving evolution: Short-term adaptations for fitnessP01AI143575 · NIAID · WEILL MEDICAL COLL OF CORNELL UNIV · PI SABINE EHRT · 2020 to 2026
$18.2M
NIAID NIH HHS P01 AI143575
6 · The paper itself

Abstract

One of the challenges in RNA-Seq studies is finding subsets of genes that share a common mechanism of action or are associated with a regulon/pathway. Existing approaches often extract modules that reflect quantitative similarities (such as genes with correlated log-fold-changes) but do not adequately capture biological significance. In this work, we propose the Dual ICA methodology, which provides an

Indexed as

Co-expression analysisGene-condition setsIndependent Component Analysis (ICA)RNA-Seq studies

Identifiers

PMID38162633
PMCPMC10757798
OpenAlexW4387346464

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.