ArticleBriefings in bioinformatics2020
An omics perspective on drug target discovery platforms.
Article in Briefings in bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers, 4 of them syntheses that pooled it.
What it found
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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
90 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Framework to identify innovative sources of value creation from platform technologies.Proceedings of the National Academy of Sciences of the United States of America · 2025Pooled it
- Machine learning-based analysis of cancer cell-derived vesicular proteins revealed significant tumor-specificity and predictive potential of extracellular vesicles for cell invasion and proliferation - A meta-analysis.Cell communication and signaling : CCS · 2023Pooled it
- Pooled it
- Meta-Analysis of Gene Popularity: Less Than Half of Gene Citations Stem from Gene Regulatory Networks.Genes · 2021Pooled it
- AI-driven computational drug design: tools, workflow and challenges.RSC advances · 2026Review
- Adh1-Programmed SNF1 Phosphogradients Decrypt Morphogenesis in Candida albicans: Chemical Interrogation Unveils Hyphal Transition Thresholds.Microbial biotechnology · 2026Article
- Optimization of potential targets for antidepressant Chinese medicines: AI and multi-omics methods.Chinese medicine · 2026Review
- From the brain cell atlas to precision neurology: a review of the application of AI-driven multi-omics in brain science.GigaScience · 2026Review
- Review
- TAPINTO: A Novel Algorithm for Tumor-Associated Antigen Prediction Based on Information about Target Overexpression.Computational and structural biotechnology journal · 2026Article
- A scalable equivariant graph network framework for precise protein function prediction.Genome biology · 2025Article
- Next-generation antifungal peptide discovery: the synergy of artificial intelligence and omics technologies.World journal of microbiology & biotechnology · 2025Review
- The changing landscape of medicinal chemistry optimization.Nature reviews. Drug discovery · 2025Review
- Review
- Bioinformatics perspectives on transcriptomics: A comprehensive review of bulk and single-cell RNA sequencing analyses.Quantitative biology (Beijing, China) · 2025Review
- Review
- Inferring Drug-Gene Relationships in Cancer Using Literature-Augmented Large Language Models.Cancer research communications · 2025Article
- Research priorities for non-invasive therapies to improve hydrocephalus outcomes.Fluids and barriers of the CNS · 2025Review
- PRMT5 inhibition has a potent anti-tumor activity against adenoid cystic carcinoma of salivary glands.Journal of experimental & clinical cancer research : CR · 2025Article
- Attention-based deep learning for accurate cell image analysis.Scientific reports · 2025Article
30 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The drug discovery process starts with identification of a disease-modifying target. This critical step traditionally begins with manual investigation of scientific literature and biomedical databases to gather evidence linking molecular target to disease, and to evaluate the efficacy, safety and commercial potential of the target. The high-throughput and affordability of current omics technologies, allowing quantitative measurements of many putative targets (e.g. DNA, RNA, protein, metabolite), has exponentially increased the volume of scientific data available for this arduous task. Therefore, computational platforms identifying and ranking disease-relevant targets from existing biomedical data sources, including omics databases, are needed. To date, more than 30 drug target discovery (DTD) platforms exist. They provide information-rich databases and graphical user interfaces to help scientists identify putative targets and pre-evaluate their therapeutic efficacy and potential side effects. Here we survey and compare a set of popular DTD platforms that utilize multiple data sources and omics-driven knowledge bases (either directly or indirectly) for identifying drug targets. We also provide a description of omics technologies and related data repositories which are important for DTD tasks.
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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.