Evidence map›Paper›PMID 26516624›Full record

ArticleBioMed research international2015

How to Use SNP_TATA_Comparator to Find a Significant Change in Gene Expression Caused by the Regulatory SNP of This Gene's Promoter via a Change in Affinity of the TATA-Binding Protein for This Promoter.

Mikhail Ponomarenko, Dmitry Rasskazov, Olga Arkova, Petr Ponomarenko, Valentin Suslov, Ludmila Savinkova, Nikolay Kolchanov

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

20 citing papers in PubMed, 40 citations in OpenAlex.

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  4. Developmental Biology: Computational and Experimental Approaches.International journal of molecular sciences · 2023
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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

7 authors at 3 institutions in 2 countries.

Mikhail PonomarenkoInstitute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia ; Department of Natural Sciences, Novosibirsk State University, Novosibirsk 630090, Russia.
Dmitry RasskazovInstitute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia.
Olga ArkovaInstitute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia.
Petr PonomarenkoChildren's Hospital Los Angeles, University of Southern California, Los Angeles, CA 90027, USA.
Valentin SuslovInstitute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia.
Ludmila SavinkovaInstitute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia.
Nikolay KolchanovInstitute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia ; Department of Natural Sciences, Novosibirsk State University, Novosibirsk 630090, Russia.
Institute of Cytology and Genetics · RUChildren's Hospital of Los Angeles · USNovosibirsk State University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of biomedical SNP markers of diseases can improve effectiveness of treatment. Genotyping of patients with subsequent searching for SNPs more frequent than in norm is the only commonly accepted method for identification of SNP markers within the framework of translational research. The bioinformatics applications aimed at millions of unannotated SNPs of the "1000 Genomes" can make this search for SNP markers more focused and less expensive. We used our Web service involving Fisher's Z-score for candidate SNP markers to find a significant change in a gene's expression. Here we analyzed the change caused by SNPs in the gene's promoter via a change in affinity of the TATA-binding protein for this promoter. We provide examples and discuss how to use this bioinformatics application in the course of practical analysis of unannotated SNPs from the "1000 Genomes" project. Using known biomedical SNP markers, we identified 17 novel candidate SNP markers nearby: rs549858786 (rheumatoid arthritis); rs72661131 (cardiovascular events in rheumatoid arthritis); rs562962093 (stroke); rs563558831 (cyclophosphamide bioactivation); rs55878706 (malaria resistance, leukopenia), rs572527200 (asthma, systemic sclerosis, and psoriasis), rs371045754 (hemophilia B), rs587745372 (cardiovascular events); rs372329931, rs200209906, rs367732974, and rs549591993 (all four: cancer); rs17231520 and rs569033466 (both: atherosclerosis); rs63750953, rs281864525, and rs34166473 (all three: malaria resistance, thalassemia).

Indexed as

Gene Expression ProfilingGene Expression RegulationGenetic Predisposition to DiseasePolymorphism, Single NucleotideAlgorithmsBinding SitesComputational BiologyGenetic MarkersGenome, HumanGenotypeHumansInternetPrecision MedicinePromoter Regions, GeneticSoftwareTATA-Box Binding ProteinGenetic MarkersTATA-Box Binding Protein

Identifiers

PMID26516624
PMCPMC4609514
OpenAlexW1912302673

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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.