ArticleMethods in molecular biology (Clifton, N.J.)2013
A guide to the current Web-based resources in pharmacogenomics.
Article in Methods in molecular biology (Clifton, N.J.), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Progress towards the integration of pharmacogenomics in practice.Human genetics · 2015Review
- Deciphering next-generation pharmacogenomics: an information technology perspective.Open biology · 2014Article
- Implications of genome-wide association studies in cancer therapeutics.British journal of clinical pharmacology · 2013Review
- Architecture of pharmacogenomic associations: structures with functional foundations or castles made of sand?Pharmacogenomics · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 4 institutions in 3 countries.
Funding
Abstract
Human genomics research has produced vast amounts of data that can be applied to or used to inform pharmacogenomic studies. The Internet is an extremely useful resource for pharmacogenomics as many Web sites provide access to data from genomic and clinical studies or host tools which can be used to interpret findings or generate hypotheses. Human genetic variation can now easily be explored or visualized through genome browsers and Web-based repositories which store the details of millions of human germ-line and somatic genetic variants. Gene expression data from many different tissue and cell types are available through Web-based repositories, and human genetic variants that associate with mRNA expression can be identified using Web data portals. Pharmacogenetic associations can be explored through publically available data repositories and the functionality of genetic variants predicted through Web-based bioinformatic tools. Furthermore, resources relating to currently used genetic tests are available online. Large clinical and population studies, many linked to medical records, can be queried for the availability of biospecimens or data. In the future, as the amount of genomic and associated clinical data increases, there is little doubt that Web-based resources will continue to evolve and overcome barriers hindering their efficient use, leading to systems-based approaches to pharmacogenomics.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.