Evidence map›Paper›PMID 26185746›Full record

ArticleGenomics data2015

An integrative approach to analyze microarray datasets for prioritization of genes relevant to lens biology and disease.

Deepti Anand, Smriti Agrawal, Archana Siddam, Hozumi Motohashi, Masayuki Yamamoto, Salil A Lachke

Open access · goldAbstract read
In one paragraph

Article in Genomics data, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 24% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

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  13. Frontiers in genetics · 2019
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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 at 2 institutions in 2 countries.

Deepti AnandDepartment of Biological Sciences, University of Delaware, Newark, DE, USA.
Smriti AgrawalDepartment of Biological Sciences, University of Delaware, Newark, DE, USA.
Archana SiddamDepartment of Biological Sciences, University of Delaware, Newark, DE, USA.
Hozumi MotohashiDepartment of Gene Expression Regulation, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.
Masayuki YamamotoDepartment of Medical Biochemistry, Graduate School of Medicine, Tohoku University, Sendai, Japan.
Salil A LachkeDepartment of Biological Sciences, University of Delaware, Newark, DE, USA ; Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE, USA.
University of Delaware · USTohoku University · JP

Funding

Predictive Modeling & Optimal Control Framework for Model-Based Epidemic Response in DelawareP20GM103446 · NIGMS · UNIVERSITY OF DELAWARE · PI Anjana Narayan Bhat · 2012 to 2026
$67.2M
POST TRANSCRIPTIONAL CONTROL OF GENE EXPRESSION IN THE LENS (LENS GENE EXPRESSIONR01EY021505 · NEI · WASHINGTON UNIVERSITY · PI LACHKE, SALIL · 2011 to 2024
$5.3M
NEI NIH HHS R01 EY021505NIGMS NIH HHS P20 GM103446
6 · The paper itself

Abstract

Microarray-based profiling represents an effective method to analyze cellular or tissue-specific gene expression on the genome-level. However, in comparative analyses between control and mutant samples, microarrays often identify a large number of differentially expressed genes, in turn making it challenging to isolate the select "high-priority candidates" that are most relevant to an observed mutant phenotype. Here, we describe an integrative approach for mouse mutant lens microarray gene expression analysis using publically accessible systems-level information such as wild-type mouse lens expression data in

Indexed as

CataractGene expressioniSyTELensMicroarrays

Identifiers

PMID26185746
PMCPMC4500531
OpenAlexW566071565

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.