ReviewPLoS computational biology2014
Towards structural systems pharmacology to study complex diseases and personalized medicine.
Review in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 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
26 citing papers in PubMed.
- Multimodal out-of-distribution individual uncertainty quantification enhances binding affinity prediction for polypharmacology.Nature machine intelligence · 2025Article
- From Gene Networks to Therapeutics: A Causal Inference and Deep Learning Approach for Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Article
- Comparison of rule- and ordinary differential equation-based dynamic model of DARPP-32 signalling network.PeerJ · 2022Article
- Mechanisms of Functional Pleiotropy of p73 in Cancer and Beyond.Frontiers in cell and developmental biology · 2021Review
- Elucidating the Inhibitory Effect of Resveratrol and Its Structural Analogs on Selected Nucleotide-Related Enzymes.Biomolecules · 2020Article
- Big Data and Artificial Intelligence Modeling for Drug Discovery.Annual review of pharmacology and toxicology · 2020Review
- On the Role of Artificial Intelligence in Genomics to Enhance Precision Medicine.Pharmacogenomics and personalized medicine · 2020Review
- Structural Insights into Characterizing Binding Sites in Epidermal Growth Factor Receptor Kinase Mutants.Journal of chemical information and modeling · 2019Article
- Coevolving residues inform protein dynamics profiles and disease susceptibility of nSNVs.PLoS computational biology · 2018Article
- REDESIGN: RDF-based Differential Signaling Framework for Precision Medicine Analytics.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2018Article
- Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology.Journal of Alzheimer's disease : JAD · 2018Review
- Network-Based Methods for Prediction of Drug-Target Interactions.Frontiers in pharmacology · 2018Review
- Envisioning the future of 'big data' biomedicine.Journal of biomedical informatics · 2017Article
- Harnessing Big Data for Systems Pharmacology.Annual review of pharmacology and toxicology · 2017Review
- Improved genome-scale multi-target virtual screening via a novel collaborative filtering approach to cold-start problem.Scientific reports · 2016Article
- A Multi-scale Computational Platform to Mechanistically Assess the Effect of Genetic Variation on Drug Responses in Human Erythrocyte Metabolism.PLoS computational biology · 2016Article
- Toward High-Throughput Predictive Modeling of Protein Binding/Unbinding Kinetics.Journal of chemical information and modeling · 2016Article
- Delineation of Polypharmacology across the Human Structural Kinome Using a Functional Site Interaction Fingerprint Approach.Journal of medicinal chemistry · 2016Article
- Toward Repurposing Metformin as a Precision Anti-Cancer Therapy Using Structural Systems Pharmacology.Scientific reports · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Genome-Wide Association Studies (GWAS), whole genome sequencing, and high-throughput omics techniques have generated vast amounts of genotypic and molecular phenotypic data. However, these data have not yet been fully explored to improve the effectiveness and efficiency of drug discovery, which continues along a one-drug-one-target-one-disease paradigm. As a partial consequence, both the cost to launch a new drug and the attrition rate are increasing. Systems pharmacology and pharmacogenomics are emerging to exploit the available data and potentially reverse this trend, but, as we argue here, more is needed. To understand the impact of genetic, epigenetic, and environmental factors on drug action, we must study the structural energetics and dynamics of molecular interactions in the context of the whole human genome and interactome. Such an approach requires an integrative modeling framework for drug action that leverages advances in data-driven statistical modeling and mechanism-based multiscale modeling and transforms heterogeneous data from GWAS, high-throughput sequencing, structural genomics, functional genomics, and chemical genomics into unified knowledge. This is not a small task, but, as reviewed here, progress is being made towards the final goal of personalized medicines for the treatment of complex diseases.
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.