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To support an ever-increasing population, modern agriculture faces numerous challenges that pose major threats to global food and energy security. Plant-associated microbes, with their many plant growth-promoting (PGP) traits, have enormous potential in helping to solve these challenges. However, the results of their use in agriculture have been variable, probably because of poor colonization. Phytomicrobiome engineering is an emerging field of synthetic biology that may offer ways to alleviate this limitation. This review highlights recent advances in both bottom-up and top-down approaches to engineering non-model bacteria and microbiomes to promote beneficial plant-microbe interactions, as well as advances in strategies to evaluate these interactions. Biosafety, biosecurity, and biocontainment strategies to address the environmental concerns associated with field use of synthetic microbes are also discussed., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Safety-by-design (SbD) is paramount for risk management in synthetic biology, with genetic safeguards being a key technology for its implementation. While attractive in theory, the integration of genetic safeguards into SbD strategies is rarely exercised in practice, despite technological advances. Here we question why and what might be done about it., (Copyright © 2020. Published by Elsevier Ltd.)

Since the beginning of the 21st Century, synthetic biology has established itself as an effective technological approach to design and engineer biological systems. Whilst research and investment continues to develop the understanding, control and engineering infrastructural platforms necessary to tackle ever more challenging systems - and to increase the precision, robustness, speed and affordability of existing solutions - hundreds of start-up companies, predominantly in the US and UK, are already translating learnings and potential applications into commercially viable tools, services and products. Start-ups and SMEs have been the predominant channel for synthetic biology commercialisation to date, facilitating rapid response to changing societal interests and market pull arising from increasing awareness of health and global sustainability issues. Private investment in start-ups across the US and UK is increasing rapidly and now totals over $12bn. Health-related biotechnology applications have dominated the commercialisation of products to date, but significant opportunities for the production of bio-derived materials and chemicals, including consumer products, are now being developed. Synthetic biology start-ups developing tools and services account for between 10% (in the UK) and ∼25% (in the US) of private investment activity. Around 20% of synthetic biology start-ups address industrial biotechnology targets, but currently, only attract ∼11% private investment. Adopting a more networked approach - linking specialists, infrastructure and ongoing research to de-risk the economic challenges of scale-up and supported by an effective long-term funding strategy - is set to transform the impact of synthetic biology and industrial biotechnology in the bioeconomy., (© 2020 The Author(s).)

The rapid pace of life sciences innovations and a growing list of nontraditional actors engaging in biological research make it challenging to develop appropriate policies to protect sensitive infrastructures. To address this challenge, we developed a five-day awareness program for security professionals, including laboratory work, site visits, and lectures., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

The eradication of infectious diseases is one of the oldest dreams of mankind. It has been materialized only once in History with smallpox in 1980. Considerable efforts are being developed against poliomyelitis viruses since 1988, but the ultimate goal of eradication is not yet achieved. Paradoxically, while the objective of having eradicated these two viral diseases is approaching, synthetic biology multiplies the prowesses of virus "neosynthesis", imperiling at least virtually the durability of these advances. This article emphasizes the potential of a new biology on one side, and the difficult reality of the fight against infections on the other., (© 2019 médecine/sciences – Inserm.)

For synthetic biology to mature, composition of devices into functional systems must become routine. This requires widespread adoption of comparable and replicable units of measurement. Interlaboratory studies organized through the International Genetically Engineered Machine (iGEM) competition show that fluorescence can be calibrated with simple, low-cost protocols, so fluorescence should no longer be published without units., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Synthetic Biology is defined as the application of engineering principles to biology. It aims to increase the speed, ease and predictability with which desirable changes and novel traits can be conferred to living cells. The initial steps in this process aim to simplify the encoding of new instructions in DNA by establishing low-level programming languages for biology. Together with advances in the laboratory that allow multiple DNA molecules to be efficiently assembled together into a desired order in a single step, this approach has simplified the design and assembly of multigene constructs and has even facilitated the automated construction of synthetic chromosomes. These advances and technologies are now being applied to plants, for which there are a growing number of software and wetware tools for the design, construction and delivery of DNA molecules and for the engineering of endogenous genes. Here we review the efforts of the past decade that have established synthetic biology workflows and tools for plants and discuss the constraints and bottlenecks of this emerging field., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Background: Leaping DNA read-and-write technologies, and extensive automation and miniaturization are radically transforming the field of biological experimentation by providing the tools that enable the cost-effective high-throughput required to address the enormous complexity of biological systems. However, standardization of the synthetic biology workflow has not kept abreast with dwindling technical and resource constraints, leading, for example, to the collection of multi-level and multi-omics large data sets that end up disconnected or remain under- or even unexploited., Purpose: In this contribution, we critically evaluate the various efforts, and the (limited) success thereof, in order to introduce standards for defining, designing, assembling, characterizing, and sharing synthetic biology parts. The causes for this success or the lack thereof, as well as possible solutions to overcome these, are discussed., Conclusion: Akin to other engineering disciplines, extensive standardization will undoubtedly speed-up and reduce the cost of bioprocess development. In this respect, further implementation of synthetic biology standards will be crucial for the field in order to redeem its promise, i.e. to enable predictable forward engineering.

Synthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems would be to improve the exchange of information about designed systems between laboratories. The synthetic biology open language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.2.0 of SBOL that builds upon version 2.1.0 published in last year's JIB special issue. In particular, SBOL 2.2.0 includes improved description and validation rules for genetic design provenance, an extension to support combinatorial genetic designs, a new class to add non-SBOL data as attachments, a new class for genetic design implementations, and a description of a methodology to describe the entire design-build-test-learn cycle within the SBOL data model.

Standards are essential to the advancement of Systems and Synthetic Biology. COMBINE provides a formal body and a centralised platform to help develop and disseminate relevant standards and related resources. The regular special issue of the Journal of Integrative Bioinformatics aims to support the exchange, distribution and archiving of these standards by providing unified, easily citable access. This paper provides an overview of existing COMBINE standards and presents developments of the last year.

People who are engineering biological organisms often find it useful to communicate in diagrams, both about the structure of the nucleic acid sequences that they are engineering and about the functional relationships between sequence features and other molecular species. Some typical practices and conventions have begun to emerge for such diagrams. The Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard for organizing and systematizing such conventions in order to produce a coherent language for expressing the structure and function of genetic designs. This document details version 2.0 of SBOL Visual, which builds on the prior SBOL Visual 1.0 standard by expanding diagram syntax to include functional interactions and molecular species, making the relationship between diagrams and the SBOL data model explicit, supporting families of symbol variants, clarifying a number of requirements and best practices, and significantly expanding the collection of diagram glyphs.

Plate-reader assays are commonly conducted to quantify the performance of synthetic biological systems. However, on the basis of a survey of 100 publications, we find that most publications do not report critical experimental settings of plate reader assays, suggesting widespread issues in their reproducibility. Specifically, critical plate reader settings, including shaking time and covering method, either vary between laboratories or are not reported by the publications. Here, we demonstrate that the settings of plate reader assays have a significant impact on bacterial growth, recombinant gene expression, and biofilm formation. Furthermore, we show that the plate reader settings affect the apparent activity, sensitivity, and chemical kinetics of synthetic constructs, as well as alter the apparent effectiveness of antibiotics. Our results suggest the critical need for consistent reporting of plate reader protocols to ensure the reproducibility of the protocols. In addition, our work provides data for the setup of plate reader protocols in synthetic biology experiments.

Standards are essential to the advancement of science and technology. In systems and synthetic biology, numerous standards and associated tools have been developed over the last 16 years. This special issue of the Journal of Integrative Bioinformatics aims to support the exchange, distribution and archiving of these standards, as well as to provide centralised and easily citable access to them.

DNA vectors serve to maintain and select recombinant DNA in cell factories, and as design complexity increases, there is a greater need for well-characterized parts and methods for their assembly. Standards in synthetic biology are top priority, but standardizing molecular cloning contrasts flexibility, and different researchers prefer and master different molecular technologies. Here, we describe a new, highly versatile and automatable standard "SEVA linkers" for vector exchange. SEVA linkers enable backbone swapping with 20 combinations of classical enzymatic restriction/ligation, Gibson isothermal assembly, uracil excision cloning, and a nicking enzyme-based methodology we term SEVA cloning. SEVA cloning is a simplistic one-tube protocol for backbone swapping directly from plasmid stock solutions. We demonstrate the different performance of 30 plasmid backbones for small molecule and protein production and obtain more than 10-fold improvement from a four-gene biosynthetic pathway and 430-fold improvement with a difficult-to-express membrane protein. The standardized linkers and protocols add to the Standard European Vectors Architecture (SEVA) resource and are freely available to the synthetic biology community.

This paper describes the development of a new data acquisition standard for synthetic biology. This comprises the creation of a methodology that is designed to capture all the data, metadata, and protocol information associated with biopart characterization experiments. The new standard, called DICOM-SB, is based on the highly successful Digital Imaging and Communications in Medicine (DICOM) standard in medicine. A data model is described which has been specifically developed for synthetic biology. The model is a modular, extensible data model for the experimental process, which can optimize data storage for large amounts of data. DICOM-SB also includes services orientated toward the automatic exchange of data and information between modalities and repositories. DICOM-SB has been developed in the context of systematic design in synthetic biology, which is based on the engineering principles of modularity, standardization, and characterization. The systematic design approach utilizes the design, build, test, and learn design cycle paradigm. DICOM-SB has been designed to be compatible with and complementary to other standards in synthetic biology, including SBOL. In this regard, the software provides effective interoperability. The new standard has been tested by experiments and data exchange between Nanyang Technological University in Singapore and Imperial College London.

In 2013, three Scientific Committees of the European Commission (EC) drafted Scientific Opinions on synthetic biology that provide an operational definition and address risk assessment methodology, safety aspects, environmental risks, knowledge gaps, and research priorities. These Opinions contribute to the international discussions on the risk governance for synthetic biology developments., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Synthetic biology is regarded as one of the key technosciences of the future. The goal of this paper is to present some fundamental considerations to enable procedures of a technology assessment (TA) of synthetic biology. To accomplish such an early "upstream" assessment of a not yet fully developed technology, a special type of TA will be considered: Prospective TA (ProTA). At the center of ProTA are the analysis and the framing of "synthetic biology," including a characterization and assessment of the technological core. The thesis is that if there is any differentia specifica giving substance to the umbrella term "synthetic biology," it is the idea of harnessing self-organization for engineering purposes. To underline that we are likely experiencing an epochal break in the ontology of technoscientific systems, this new type of technology is called "late-modern technology." -I start this paper by analyzing the three most common visions of synthetic biology. Then I argue that one particular vision deserves more attention because it underlies the others: the vision of self-organization. I discuss the inherent limits of this new type of late-modern technology in the attempt to control and monitor possible risk issues. I refer to Hans Jonas' ethics and his early anticipation of the risks of a novel type of technology. I end by drawing conclusions for the approach of ProTA towards an early societal shaping of synthetic biology.

Research is communicated more effectively and reproducibly when articles depict genetic designs consistently and fully disclose the complete sequences of all reported constructs. ACS Synthetic Biology is now providing authors with updated guidance and piloting a new tool and publication workflow that facilitate compliance with these recommended practices and standards for visual representation and data exchange.

Standards are important to synthetic biology because they enable exchange and reproducibility of genetic designs. This paper describes a procedure for converting between two standards: the Systems Biology Markup Language (SBML) and the Synthetic Biology Open Language (SBOL). SBML is a standard for behavioral models of biological systems at the molecular level. SBOL describes structural and basic qualitative behavioral aspects of a biological design. Converting SBML to SBOL enables a consistent connection between behavioral and structural information for a biological design. The conversion process described in this paper leverages Systems Biology Ontology (SBO) annotations to enable inference of a designs qualitative function.

The Synthetic Biology Open Language (SBOL) is a standard that enables collaborative engineering of biological systems across different institutions and tools. SBOL is developed through careful consideration of recent synthetic biology trends, real use cases, and consensus among leading researchers in the field and members of commercial biotechnology enterprises. We demonstrate and discuss how a set of SBOL-enabled software tools can form an integrated, cross-organizational workflow to recapitulate the design of one of the largest published genetic circuits to date, a 4-input AND sensor. This design encompasses the structural components of the system, such as its DNA, RNA, small molecules, and proteins, as well as the interactions between these components that determine the system's behavior/function. The demonstrated workflow and resulting circuit design illustrate the utility of SBOL 2.0 in automating the exchange of structural and functional specifications for genetic parts, devices, and the biological systems in which they operate.

Synthetic biology aims to apply engineering principles to the design and modification of biological systems and to the construction of biological parts and devices. The ability to programme cells by providing new instructions written in DNA is a foundational technology of the field. Large-scale de novo DNA synthesis has accelerated synthetic biology by offering custom-made molecules at ever decreasing costs. However, for large fragments and for experiments in which libraries of DNA sequences are assembled in different combinations, assembly in the laboratory is still desirable. Biological assembly standards allow DNA parts, even those from multiple laboratories and experiments, to be assembled together using the same reagents and protocols. The adoption of such standards for plant synthetic biology has been cohesive for the plant science community, facilitating the application of genome editing technologies to plant systems and streamlining progress in large-scale, multi-laboratory bioengineering projects., (© 2016 The Author(s). published by Portland Press Limited on behalf of the Biochemical Society.)

Factors that shape actual research practices - 'social and institutional context' - typically are missing from considerations of synthetic biology R&D-related risk and containment. We argue that analyzing context is essential in identifying circumstances that create, amplify, or diminish risk, and in revealing new opportunities for avoiding or managing those risks., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Metabolic pathways can be engineered to maximize the synthesis of various products of interest. With the advent of computational systems biology, this endeavour is usually carried out through in silico theoretical studies with the aim to guide and complement further in vitro and in vivo experimental efforts. Clearly, what counts is the result in vivo, not only in terms of maximal productivity but also robustness against environmental perturbations. Engineering an organism towards an increased production flux, however, often compromises that robustness. In this contribution, we review and investigate how various analytical approaches used in metabolic engineering and synthetic biology are related to concepts developed by systems and control engineering. While trade-offs between production optimality and cellular robustness have already been studied diagnostically and statically, the dynamics also matter. Integration of the dynamic design aspects of control engineering with the more diagnostic aspects of metabolic, hierarchical control and regulation analysis is leading to the new, conceptual and operational framework required for the design of robust and productive dynamic pathways., (© 2016 The Author(s).)

Synthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long development times, high rates of failure, and poor reproducibility. One method to ameliorate these problems would be to improve the exchange of information about designed systems between laboratories. The Synthetic Biology Open Language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards. This document details version 2.0 of SBOL, introducing a standardized format for the electronic exchange of information on the structural and functional aspects of biological designs. The standard has been designed to support the explicit and unambiguous description of biological designs by means of a well defined data model. The standard also includes rules and best practices on how to use this data model and populate it with relevant design details. The publication of this specification is intended to make these capabilities more widely accessible to potential developers and users in the synthetic biology community and beyond.

Standards shape our everyday life. From nuts and bolts to electronic devices and technological processes, standardised products and processes are all around us. Standards have technological and economic benefits, such as making information exchange, production, and services more efficient. However, novel, innovative areas often either lack proper standards, or documents about standards in these areas are not available from a centralised platform or formal body (such as the International Standardisation Organisation). Systems and synthetic biology is a relatively novel area, and it is only in the last decade that the standardisation of data, information, and models related to systems and synthetic biology has become a community-wide effort. Several open standards have been established and are under continuous development as a community initiative. COMBINE, the ‘COmputational Modeling in BIology’ NEtwork has been established as an umbrella initiative to coordinate and promote the development of the various community standards and formats for computational models. There are yearly two meeting, HARMONY (Hackathons on Resources for Modeling in Biology), Hackathon-type meetings with a focus on development of the support for standards, and COMBINE forums, workshop-style events with oral presentations, discussion, poster, and breakout sessions for further developing the standards. For more information see http://co.mbine.org/. So far the different standards were published and made accessible through the standards’ web- pages or preprint services. The aim of this special issue is to provide a single, easily accessible and citable platform for the publication of standards in systems and synthetic biology. This special issue is intended to serve as a central access point to standards and related initiatives in systems and synthetic biology, it will be published annually to provide an opportunity for standard development groups to communicate updated specifications.

Synthetic biology applications in biosensing, bioremediation, and biomining envision the use of engineered microbes beyond a contained laboratory. Deployment of such microbes in the environment raises concerns of unchecked cellular proliferation or unwanted spread of synthetic genes. While antibiotic-resistant plasmids are the most utilized vectors for introducing synthetic genes into bacteria, they are also inherently insecure, acting naturally to propagate DNA from one cell to another. To introduce security into bacterial synthetic biology, we here took on the task of completely reformatting plasmids to be dependent on their intended host strain and inherently disadvantageous for others. Using conditional origins of replication, rich-media compatible auxotrophies, and toxin-antitoxin pairs we constructed a mutually dependent host-plasmid platform, called GeneGuard. In this, replication initiators for the R6K or ColE2-P9 origins are provided in trans by a specified host, whose essential thyA or dapA gene is translocated from a genomic to a plasmid location. This reciprocal arrangement is stable for at least 100 generations without antibiotic selection and is compatible for use in LB medium and soil. Toxin genes ζ or Kid are also employed in an auxiliary manner to make the vector disadvantageous for strains not expressing their antitoxins. These devices, in isolation and in concert, severely reduce unintentional plasmid propagation in E. coli and B. subtilis and do not disrupt the intended E. coli host's growth dynamics. Our GeneGuard system comprises several versions of modular cargo-ready vectors, along with their requisite genomic integration cassettes, and is demonstrated here as an efficient vector for heavy-metal biosensors.

The re-use of previously validated designs is critical to the evolution of synthetic biology from a research discipline to an engineering practice. Here we describe the Synthetic Biology Open Language (SBOL), a proposed data standard for exchanging designs within the synthetic biology community. SBOL represents synthetic biology designs in a community-driven, formalized format for exchange between software tools, research groups and commercial service providers. The SBOL Developers Group has implemented SBOL as an XML/RDF serialization and provides software libraries and specification documentation to help developers implement SBOL in their own software. We describe early successes, including a demonstration of the utility of SBOL for information exchange between several different software tools and repositories from both academic and industrial partners. As a community-driven standard, SBOL will be updated as synthetic biology evolves to provide specific capabilities for different aspects of the synthetic biology workflow.

The BioBrick idea was developed to introduce the engineering principles of abstraction and standardization into synthetic biology. BioBricks are DNA sequences that serve a defined biological function and can be readily assembled with any other BioBrick parts to create new BioBricks with novel properties. In order to achieve this, several assembly standards can be used. Which assembly standards a BioBrick is compatible with, depends on the prefix and suffix sequences surrounding the part. In this chapter, five of the most common assembly standards will be described, as well as some of the most used assembly techniques, cloning procedures, and a presentation of the available software tools that can be used for deciding on the best method for assembling of different BioBricks, and searching for BioBrick parts in the Registry of Standard Biological Parts database.

Overlap-directed DNA assembly methods allow multiple DNA parts to be assembled together in one reaction. These methods, which rely on sequence homology between the ends of DNA parts, have become widely adopted in synthetic biology, despite being incompatible with a key principle of engineering: modularity. To answer this, we present MODAL: a Modular Overlap-Directed Assembly with Linkers strategy that brings modularity to overlap-directed methods, allowing assembly of an initial set of DNA parts into a variety of arrangements in one-pot reactions. MODAL is accompanied by a custom software tool that designs overlap linkers to guide assembly, allowing parts to be assembled in any specified order and orientation. The in silico design of synthetic orthogonal overlapping junctions allows for much greater efficiency in DNA assembly for a variety of different methods compared with using non-designed sequence. In tests with three different assembly technologies, the MODAL strategy gives assembly of both yeast and bacterial plasmids, composed of up to five DNA parts in the kilobase range with efficiencies of between 75 and 100%. It also seamlessly allows mutagenesis to be performed on any specified DNA parts during the process, allowing the one-step creation of construct libraries valuable for synthetic biology applications.

In this article, we relate the story of Synthetic Biology's birth, from the perspective of a co-founder, and consider its original premise--that standardization and abstraction of biological components will unlock the full potential of biological engineering. The standardization ideas of Synthetic Biology emerged in the late 1990s from a convergence of research on cellular computing, and were motivated by an array of applications from tissue regeneration to bio-sensing to mathematical programming. As the definition of Synthetic Biology has grown to be synonymous with Biological Engineering and Biotechnology, the field has lost sight of the fact that its founding premise has not yet been validated. While the value of standardization has been proven in many other engineering disciplines, none of them involve self-replicating systems. The engineering of self-replicating systems will likely benefit from standardization, and also by embracing the forces of evolution that inexorably shape such systems., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

One of the most influential philosophers of the 20th century, Martin Heidegger (1889-1976), died prior to the remarkable cloning of the sheep Dolly and before Dr. Venter started his experiments on creating synthetic life, and he never explicitly discussed living technologies. However, by reinterpreting his notion of "modern technology," this article shows how it is possible to philosophically assess living technologies and to recognize ways in which Heidegger anticipated this phenomenon with his notion of cybernetics. The interpretation elucidates the fundamental process of technology becoming living and simultaneously presents living technology as the ultimate technology. The thesis of this article is that living technology is not just one more technology; rather, it is the perfection of technology as understood by Aristotle. Aristotle's thinking is in this way a key example of a profound reassessment of nature and technology. Aristotle clearly separates these two domains of being in his definition, but in doing so, he also connects them to one another in a highly influential way. Following this line of thought, the article finally offers an original perspective involving renewed respect for the perpetual self-unfolding nature of living technology.

The life sciences present a politically and ethically sensitive area of technology development. NBIC convergence-the convergence of nanotechnology, biotechnology, and information and cognitive technology-presents an increased interaction between the biological and physical sciences. As a result the bio-debate is no longer dominated by biotechnology, but driven by NBIC convergence. NBIC convergence enables two bioengineering megatrends: "biology becoming technology" and "technology becoming biology." The notion of living technologies captures the latter megatrend. Accordingly, living technology presents a politically and ethically sensitive area. This implies that governments sooner or later are faced with the challenge of both promoting and regulating the development of living technology. This article describes four current political models to deal with innovation promotion and risk regulation. Based on two specific developments in the field of living technologies-(psycho)physiological computing and synthetic biology-we reflect on appropriate governance strategies for living technologies. We conclude that recent pleas for anticipatory and deliberative governance tend to neglect the need for anticipatory regulation as a key factor in guiding the development of the life sciences from a societal perspective. In particular, when it is expected that a certain living technology will radically challenge current regulatory systems, one should opt for just such a more active biopolitical approach.

Just over two years ago there was an article in Nature entitled "Five Hard Truths for Synthetic Biology". Since then, the field has moved on considerably. A number of economic commentators have shown that synthetic biology very significant industrial potential. This paper addresses key issues in relation to the state of play regarding synthetic biology. It first considers the current background to synthetic biology, whether it is a legitimate field and how it relates to foundational biological sciences. The fact that synthetic biology is a translational field is discussed and placed in the context of the industrial translation process. An important aspect of synthetic biology is platform technology, this topic is also discussed in some detail. Finally, examples of application areas are described., (Copyright © 2012. Published by Elsevier B.V.)

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., (Copyright © 2012 WILEY Periodicals, Inc.)