ArticleBioEssays : news and reviews in molecular, cellular and developmental biology2012
Scientific discovery as a combinatorial optimisation problem: how best to navigate the landscape of possible experiments?
Article in BioEssays : news and reviews in molecular, cellular and developmental biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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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.
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Who cites it
22 citing papers in PubMed.
- How far can you go? Extrapolating values of catalytic activity from known protein landscapes in natural and directed evolution.Chemical Society reviews · 2026Review
- A Direct Relationship Between 'Blood Stasis' and Fibrinaloid Microclots in Chronic, Inflammatory, and Vascular Diseases, and Some Traditional Natural Products Approaches to Treatment.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Intelligent host engineering for metabolic flux optimisation in biotechnology.The Biochemical journal · 2021Review
- Deep learning and generative methods in cheminformatics and chemical biology: navigating small molecule space intelligently.The Biochemical journal · 2020Review
- GeneORator: An Effective Strategy for Navigating Protein Sequence Space More Efficiently through Boolean OR-Type DNA Libraries.ACS synthetic biology · 2019Article
- Understanding dynamics of coherent Ising machines through simulation of large-scale 2D Ising models.Nature communications · 2018Article
- Ultra-high throughput functional enrichment of large monoamine oxidase (MAO-N) libraries by fluorescence activated cell sorting.The Analyst · 2018Article
- In silico engineering ofPeerJ · 2018Article
- Major involvement of bacterial components in rheumatoid arthritis and its accompanying oxidative stress, systemic inflammation and hypercoagulability.Experimental biology and medicine (Maywood, N.J.) · 2017Review
- Evolutionary algorithms and synthetic biology for directed evolution: commentary on "on the mapping of genotype to phenotype in evolutionary algorithms" by Peter A. Whigham, Grant Dick, and James Maclaurin.Genetic programming and evolvable machines · 2017Article
- A Bacterial Component to Alzheimer's-Type Dementia Seen via a Systems Biology Approach that Links Iron Dysregulation and Inflammagen Shedding to Disease.Journal of Alzheimer's disease : JAD · 2016Review
- Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently.Chemical Society reviews · 2015Review
- The virtue of innovation: innovation through the lenses of biological evolution.Journal of the Royal Society, Interface · 2015Article
- Individuality, phenotypic differentiation, dormancy and 'persistence' in culturable bacterial systems: commonalities shared by environmental, laboratory, and clinical microbiology.F1000Research · 2015Review
- SpeedyGenes: an improved gene synthesis method for the efficient production of error-corrected, synthetic protein libraries for directed evolution.Protein engineering, design & selection : PEDS · 2014Article
- Metabolomics and systems pharmacology: why and how to model the human metabolic network for drug discovery.Drug discovery today · 2014Review
- A strategy for finding the optimal scale of plant core collection based on Monte Carlo simulation.TheScientificWorldJournal · 2014Article
- How drugs get into cells: tested and testable predictions to help discriminate between transporter-mediated uptake and lipoidal bilayer diffusion.Frontiers in pharmacology · 2014Review
- Iterative refinement of a binding pocket model: active computational steering of lead optimization.Journal of medicinal chemistry · 2012Article
- Exploiting genomic knowledge in optimising molecular breeding programmes: algorithms from evolutionary computing.PloS one · 2012Article
Corrections and comments
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Authors and funding
1 author.
Funding
Abstract
A considerable number of areas of bioscience, including gene and drug discovery, metabolic engineering for the biotechnological improvement of organisms, and the processes of natural and directed evolution, are best viewed in terms of a 'landscape' representing a large search space of possible solutions or experiments populated by a considerably smaller number of actual solutions that then emerge. This is what makes these problems 'hard', but as such these are to be seen as combinatorial optimisation problems that are best attacked by heuristic methods known from that field. Such landscapes, which may also represent or include multiple objectives, are effectively modelled in silico, with modern active learning algorithms such as those based on Darwinian evolution providing guidance, using existing knowledge, as to what is the 'best' experiment to do next. An awareness, and the application, of these methods can thereby enhance the scientific discovery process considerably. This analysis fits comfortably with an emerging epistemology that sees scientific reasoning, the search for solutions, and scientific discovery as Bayesian processes.
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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.