Evidence map›Paper›PMID 39636731›Full record

ArticleSTAR protocols2024

Protocol for identifying key genes using network-based approach as an alternative to differential expression analysis.

Piyush Agrawal, Sridhar Hannenhalli

Abstract read
In one paragraph

Article in STAR protocols, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Piyush AgrawalDepartment of Medical Research, SRM Medical College Hospital & Research Centre, SRMIST, Kattankulathur, Chennai, India. Electronic address: piyusha@srmist.edu.in.
Sridhar HannenhalliCancer Data Science Lab, National Cancer Institute, NIH, Bethesda, MD, USA. Electronic address: sridhar.hannenhalli@nih.gov.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In a variety of biological contexts, characterizing genes associated with disease etiology and mediating global transcriptomic change is a key initial step. Here, we present a protocol to identify such key genes using our tool "PathExt," a tool that implements a network-based approach. We describe steps for installing libraries, preparing input data and detailed procedures for running PathExt, and characterizing differential pathways and key genes based on ripple centrality scores. For complete details on the use and execution of this protocol, please refer to Agrawal et al.

Indexed as

Gene Expression ProfilingGene Regulatory NetworksComputational BiologyHumansSoftwareTranscriptomeBioinformaticsCancerComputer sciencesGenomicsSystems biology

Identifiers

PMID39636731
PMCPMC11664135

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.