ReviewPharmacogenomics2011
Systems biology data analysis methodology in pharmacogenomics.
Review in Pharmacogenomics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 15 citations in OpenAlex.
- Pharmacogenomic characterization of gemcitabine response--a framework for data integration to enable personalized medicine.Pharmacogenetics and genomics · 2014Trial
- Multiple sclerosis and computational biology (Review).Biomedical reports · 2022Review
- A pharmacogenetic risk score for the evaluation of major depression severity under treatment with antidepressants.Drug development research · 2020Article
- Analysis of high-resolution 3D intrachromosomal interactions aided by Bayesian network modeling.Proceedings of the National Academy of Sciences of the United States of America · 2017Article
- Toward a Global Roadmap for Precision Medicine in Psychiatry: Challenges and Opportunities.Omics : a journal of integrative biology · 2016Review
- Genome-wide multi-omics profiling of colorectal cancer identifies immune determinants strongly associated with relapse.Frontiers in genetics · 2013Article
- The success of pharmacogenomics in moving genetic association studies from bench to bedside: study design and implementation of precision medicine in the post-GWAS era.Human genetics · 2012Review
- Integrative systems biology approaches in asthma pharmacogenomics.Pharmacogenomics · 2012Review
- Using systems approaches to address challenges for clinical implementation of pharmacogenomics.Wiley interdisciplinary reviews. Systems biology and medicineReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Pharmacogenetics aims to elucidate the genetic factors underlying the individual's response to pharmacotherapy. Coupled with the recent (and ongoing) progress in high-throughput genotyping, sequencing and other genomic technologies, pharmacogenetics is rapidly transforming into pharmacogenomics, while pursuing the primary goals of identifying and studying the genetic contribution to drug therapy response and adverse effects, and existing drug characterization and new drug discovery. Accomplishment of both of these goals hinges on gaining a better understanding of the underlying biological systems; however, reverse-engineering biological system models from the massive datasets generated by the large-scale genetic epidemiology studies presents a formidable data analysis challenge. In this article, we review the recent progress made in developing such data analysis methodology within the paradigm of systems biology research that broadly aims to gain a 'holistic', or 'mechanistic' understanding of biological systems by attempting to capture the entirety of interactions between the components (genetic and otherwise) of the system.
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.