Evidence map›Paper›PMID 37484779›Full record

ArticleIn silico pharmacology2023

Anamika Yadav, Shivani Srivastava, Shivani Tyagi, Neelam Krishna, Pramod Katara

Abstract read
In one paragraph

Article in In silico pharmacology, 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
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

5 authors.

Anamika YadavComputational Omics Lab, Centre of Bioinformatics, University of Allahabad, Prayagraj, 211002 India.ORCID 0000-0001-9141-7319
Shivani SrivastavaComputational Omics Lab, Centre of Bioinformatics, University of Allahabad, Prayagraj, 211002 India.
Shivani TyagiComputational Omics Lab, Centre of Bioinformatics, University of Allahabad, Prayagraj, 211002 India.
Neelam KrishnaComputational Omics Lab, Centre of Bioinformatics, University of Allahabad, Prayagraj, 211002 India.
Pramod KataraComputational Omics Lab, Centre of Bioinformatics, University of Allahabad, Prayagraj, 211002 India.ORCID 0000-0002-3444-2822

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drugs pharmacology is defined by pharmacokinetics and pharmacodynamics and both of them are affected by genetic variability. Genetic variability varies from population to population, and sometimes even within the population, it exists. Single nucleotide polymorphisms (SNPs) are one of the major genetic variability factors which are found to be associated with the pharmacokinetics and pharmacodynamics process of a drug and are responsible for variable drug response and clinical phenotypes. Studies of SNPs can help to perform genome-wide association studies for their association with pharmacological and clinical events, at the same time; their information can direct genome-wide association studies for their use as biomarkers. With the aim to mine and characterize Indian populated SNPs of pharmacological and clinical importance. Two hundred six candidate SNPs belonging to 43 genes were retrieved from Indian Genome Variation Database. The distribution pattern of considered SNPs was observed against all five world super-populations (AFR, AMR, EAS, EUR, and SAS). Further, their annotation was done through SNP-nexus by considering Human genome reference builds - hg38, pharmacological and clinical information was supplemented by PharmGKB and ClinVar database. At last, to find out the association between SNPs linkage disequilibrium was observed in terms of r Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-023-00154-4.

Indexed as

Drug responseHaplotypeLinkage disequilibriumMolecular markerSingle nucleotide polymorphisms

Identifiers

PMID37484779
PMCPMC10356698

What OpenQuestion holds

Textmetadata
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.