Evidence map›Paper›PMID 25030607›Full record

ArticleOpen biology2014

Deciphering next-generation pharmacogenomics: an information technology perspective.

George Potamias, Kleanthi Lakiotaki, Theodora Katsila, Ming Ta Michael Lee, Stavros Topouzis, David N Cooper, George P Patrinos

Abstract read
In one paragraph

Article in Open biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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  14. Article
  15. Whole genome sequencing in pharmacogenomics.Frontiers in pharmacology · 2015
    Article
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.

George PotamiasInstitute of Computer Science, Foundation for Research and Technology Hellas, Crete, Greece.
Kleanthi LakiotakiInstitute of Computer Science, Foundation for Research and Technology Hellas, Crete, Greece.
Theodora KatsilaDepartment of Pharmacy, School of Health Sciences, University of Patras, University Campus, Rion, Patras, Greece.
Ming Ta Michael LeeLaboratory for International Alliance on Genomic Medicine, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
Stavros TopouzisDepartment of Pharmacy, School of Health Sciences, University of Patras, University Campus, Rion, Patras, Greece.
David N CooperInstitute of Medical Genetics, School of Medicine, Cardiff University, Cardiff, UK.
George P PatrinosDepartment of Pharmacy, School of Health Sciences, University of Patras, University Campus, Rion, Patras, Greece gpatrinos@upatras.gr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the post-genomic era, the rapid evolution of high-throughput genotyping technologies and the increased pace of production of genetic research data are continually prompting the development of appropriate informatics tools, systems and databases as we attempt to cope with the flood of incoming genetic information. Alongside new technologies that serve to enhance data connectivity, emerging information systems should contribute to the creation of a powerful knowledge environment for genotype-to-phenotype information in the context of translational medicine. In the area of pharmacogenomics and personalized medicine, it has become evident that database applications providing important information on the occurrence and consequences of gene variants involved in pharmacokinetics, pharmacodynamics, drug efficacy and drug toxicity will become an integral tool for researchers and medical practitioners alike. At the same time, two fundamental issues are inextricably linked to current developments, namely data sharing and data protection. Here, we discuss high-throughput and next-generation sequencing technology and its impact on pharmacogenomics research. In addition, we present advances and challenges in the field of pharmacogenomics information systems which have in turn triggered the development of an integrated electronic 'pharmacogenomics assistant'. The system is designed to provide personalized drug recommendations based on linked genotype-to-phenotype pharmacogenomics data, as well as to support biomedical researchers in the identification of pharmacogenomics-related gene variants. The provisioned services are tuned in the framework of a single-access pharmacogenomics portal.

Indexed as

GenomeGenomicsHigh-Throughput Nucleotide SequencingHumansPharmacogeneticsPrecision Medicinedrug metabolismgene variantsinformatics solutionsmicroattributionpersonalized pharmacogenomics profilewhole-genome sequencing

Identifiers

PMID25030607
PMCPMC4118603

What OpenQuestion holds

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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.