ReviewComputational and structural biotechnology journal2016
Computational approaches in target identification and drug discovery.
Review in Computational and structural biotechnology journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 104 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.
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Who cites it
104 citing papers in PubMed.
- Machine Learning and Molecular Modeling Strategy for the Identification of CNS-Active Acetylcholinesterase Inhibitors.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Biotinylated Diaryl Isoxazole Derivatives with Enhanced Janus Kinase 1 Inhibitory, Antiproliferative, and Apoptotic Activities in Cancer Cells.ACS omega · 2026Article
- Synthetic Elaboration, DFT Profiling, and Molecular-Dynamics-Guided Computational Validation Toward Anti-Diabetic Therapeutics: Tailored Pyrimidine-Derived Pyrazole-Thiadiazole Hybrid Scaffolds.Pharmaceuticals (Basel, Switzerland) · 2026Article
- The Venom Revolution in Biomedicine: Unlocking Nature's Toxin Toolkit for Therapeutic Innovation.Toxicology reports · 2026Review
- Natural Products in Epilepsy Treatment: From Traditional Medicine Towards Computational Drug Discovery.Current issues in molecular biology · 2026Review
- Molecular docking: a computational approach for the discovery of novel targets against visceral leishmaniasis.Journal of molecular modeling · 2026Review
- Highly Drug-Resistant Escherichia coli from Hospital Wastewater with Several Evolutionary Mutations: An Integrated Insights from Molecular, Computational, and Biophysics.Molecular biotechnology · 2026Article
- Dipeptidyl Peptidase 4 Inhibitors: Novel Therapeutic Agents in the Management of Type II Diabetes Mellitus.Pharmacoepidemiology and drug safety · 2025Review
- Targeting cyclin-dependent kinase 11: a computational approach for natural anti-cancer compound discovery.Molecular diversity · 2025Article
- Computational Investigation of the Potential Antileishmanial Mechanism of the Nitroindazole Derivative VATR131.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Genetic Characterization ofToxins · 2025Article
- Review
- Computational analysis of luteolin, apigenin and their derivatives from Allophylus africanus as potential inhibitors of plasmepsin II a malaria target.BMC chemistry · 2025Article
- From Data to Cure: A Comprehensive Exploration of Multi-omics Data Analysis for Targeted Therapies.Molecular biotechnology · 2025Review
- Advanced Artificial Intelligence Technologies Transforming Contemporary Pharmaceutical Research.Bioengineering (Basel, Switzerland) · 2025Review
- Artificial Intelligence-Driven Innovations in Oncology Drug Discovery: Transforming Traditional Pipelines and Enhancing Drug Design.Drug design, development and therapy · 2025Review
- Article
- Identification of molecular targets of Trigonelline for treating breast cancer through network pharmacology and bioinformatics-based prediction.Molecular diversity · 2024Article
- Indian Medicinal Plant-Derived Phytochemicals as Potential Antidotes for Snakebite: A Pharmacoinformatic Study of Atrolysin Inhibitors.International journal of molecular sciences · 2024Article
- Medicinal plants as a potential resource for the discovery of novel structures towards cancer drug resistance treatment.Heliyon · 2024Review
44 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the big data era, voluminous datasets are routinely acquired, stored and analyzed with the aim to inform biomedical discoveries and validate hypotheses. No doubt, data volume and diversity have dramatically increased by the advent of new technologies and open data initiatives. Big data are used across the whole drug discovery pipeline from target identification and mechanism of action to identification of novel leads and drug candidates. Such methods are depicted and discussed, with the aim to provide a general view of computational tools and databases available. We feel that big data leveraging needs to be cost-effective and focus on personalized medicine. For this, we propose the interplay of information technologies and (chemo)informatic tools on the basis of their synergy.
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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.