ReviewTrends in genetics : TIG2018
Genetic-Driven Druggable Target Identification and Validation.
Review in Trends in genetics : TIG, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 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
31 citing papers in PubMed.
- Moving Mendelian Randomization From Traditional Risk Factors to Molecular Targets for Drug Development and Clinical Trials in Nephrology.Kidney international reports · 2026Review
- AI-powered precision medicine: utilizing genetic risk factor optimization to revolutionize healthcare.NAR genomics and bioinformatics · 2025Review
- Drug target assessments: classifying target modulation and associated health effects using multi-level BERT-based classification models.Bioinformatics advances · 2025Article
- Liangxue Qushi Zhiyang Decoction Inhibits Atopic Dermatitis in Mice via FcMediators of inflammation · 2025Article
- The computationally guided design of selective targeters of multiple proteins (STaMPs) as a new opportunity for small molecule drug discovery.Frontiers in pharmacology · 2025Review
- Druggable targets for Parkinson's disease: transcriptomics based Mendelian randomization study.Scientific reports · 2024Article
- Review
- DBPP-Predictor: a novel strategy for prediction of chemical drug-likeness based on property profiles.Journal of cheminformatics · 2024Article
- Non-Coding RNAs: Foes or Friends for Targeting Tumor Microenvironment.Non-coding RNA · 2023Review
- Comparative neurogenetics of dog behavior complements efforts towards human neuropsychiatric genetics.Human genetics · 2023Review
- Omics approaches to understanding the efficacy and safety of disease-modifying treatments in multiple sclerosis.Frontiers in genetics · 2023Review
- A compendium of validated pain genes.WIREs mechanisms of disease · 2022Review
- Enhancer promoter interactome and Mendelian randomization identify network of druggable vascular genes in coronary artery disease.Human genomics · 2022Article
- Knowledge-based approaches to drug discovery for rare diseases.Drug discovery today · 2022Review
- Canine osteosarcoma in comparative oncology: Molecular mechanisms through to treatment discovery.Frontiers in veterinary science · 2022Review
- Text Mining Protocol to Retrieve Significant Drug-Gene Interactions from PubMed Abstracts.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Combining Human Genetics of Multiple Sclerosis with Oxidative Stress Phenotype for Drug Repositioning.Pharmaceutics · 2021Article
- Anti-Irritant Strategy against Retinol Based on the Genetic Analysis of Korean Population: A Genetically Guided Top-Down Approach.Pharmaceutics · 2021Article
- De novo variation in bipolar disorder.Molecular psychiatry · 2021Article
- Druggable hot spots in trypanothione reductase: novel insights and opportunities for drug discovery revealed by DRUGpy.Journal of computer-aided molecular design · 2021Article
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.
Funding
Abstract
Choosing the right biological target is the critical primary decision for the development of new drugs. Systematic genetic association testing of both human diseases and quantitative traits, along with resultant findings of coincident associations between them, is becoming a powerful approach to infer drug targetable candidates and generate in vitro tests to identify compounds that can modulate them therapeutically. Here, we discuss opportunities and challenges, and infer criteria for the optimal use of genetic findings in the drug discovery pipeline.
Indexed as
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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.