ReviewTrends in pharmacological sciences2011
Systems genetics for drug target discovery.
Review in Trends in pharmacological sciences, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled 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.
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
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 46 citations in OpenAlex.
- Genetic analysis of quantitative phenotypes in AD and MCI: imaging, cognition and biomarkers.Brain imaging and behavior · 2014Pooled it
- A new paradigm for drug discovery in the treatment of complex diseases: drug discovery and optimization.Chinese medicine · 2025Review
- The future of metronomic chemotherapy: experimental and computational approaches of drug repurposing.Pharmacological reports : PR · 2025Review
- Leveraging pleiotropy for the improved treatment of psychiatric disorders.Molecular psychiatry · 2025Review
- Revolutionising Neurological Therapeutics: Investigating Drug Repurposing Strategies.CNS & neurological disorders drug targets · 2025Review
- Multi-level advances in databases related to systems pharmacology in traditional Chinese medicine: a 60-year review.Frontiers in pharmacology · 2023Review
- Repurposing Drugs via Network Analysis: Opportunities for Psychiatric Disorders.Pharmaceutics · 2022Review
- Identification of Candidate Biomarkers for Idiopathic Thrombocytopenic Purpura by Bioinformatics Analysis of Microarray Data.Iranian journal of pharmaceutical research : IJPR · 2020Article
- Co-expression networks reveal the tissue-specific regulation of transcription and splicing.Genome research · 2017Article
- Integrated Computational Analysis of Genes Associated with Human Hereditary Insensitivity to Pain. A Drug Repurposing Perspective.Frontiers in molecular neuroscience · 2017Article
- In silico frameworks for systematic pre-clinical screening of potential anti-leukemia therapeutics.Expert opinion on drug discovery · 2016Review
- Integrative analysis of cancer genes in a functional interactome.Scientific reports · 2016Article
- Genetic studies of quantitative MCI and AD phenotypes in ADNI: Progress, opportunities, and plans.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2015Review
- Pathways to neurodegeneration: mechanistic insights from GWAS in Alzheimer's disease, Parkinson's disease, and related disorders.American journal of neurodegenerative disease · 2013Review
- Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review.Pharmacology & therapeutics · 2013Review
- Drug discovery from marine microbes.Microbial ecology · 2013Review
- Navigating traditional chinese medicine network pharmacology and computational tools.Evidence-based complementary and alternative medicine : eCAM · 2013Article
- Genome-wide pathway analysis of memory impairment in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort implicates gene candidates, canonical pathways, and networks.Brain imaging and behavior · 2012Article
- Pathway analysis of genomic data: concepts, methods, and prospects for future development.Trends in genetics : TIG · 2012Review
- Network systems biology for targeted cancer therapies.Chinese journal of cancer · 2012Review
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
The collection and analysis of genomic data has the potential to reveal novel druggable targets by providing insight into the genetic basis of disease. However, the number of drugs targeting new molecular entities, approved by the US Food and Drug Administration has not increased in the years since the collection of genomic data has become commonplace. The paucity of translatable results can be partly attributed to conventional analysis methods that test one gene at a time in an effort to identify disease-associated factors as candidate drug targets. By disengaging genetic factors from their position within the genetic regulatory system, much of the information stored within the genomic data set is lost. Here we discuss how genomic data is used to identify disease-associated genes or genomic regions, how disease-associated regions are validated as functional targets, and the role network analysis can play in bridging the gap between data generation and effective drug target identification.
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.