Choosing an appropriate modelling framework for analysing multispecies co-culture cell biology experiments

In vitro cell biology assays play a crucial role in informing our understanding of the migratory, proliferative and invasive properties of many cell types in different biological contexts. While mono-culture assays involve the study of a population of cells composed of a single cell type, co-culture assays study a population of cells composed of multiple cell types (or subpopulations of cells). Such co-culture assays can provide more realistic insights into many biological processes including tissue repair, tissue regeneration and malignant spreading. Typically, system parameters, such as motility and proliferation rates, are estimated by calibrating a mathematical or computational model to the observed experimental data. However, parameter estimates can be highly sensitive to the choice of model and modelling framework. This observation motivates us to consider the fundamental question of how we can best choose a model to facilitate accurate parameter estimation for a particular assay. In this work we describe three mathematical models of mono-culture and co-culture assays that include different levels of spatial detail. We study various spatial summary statistics to explore if they can be used to distinguish between the suitability of each model over a range of parameter space. Our results for mono-culture experiments are promising, in that we suggest two spatial statistics that can be used to direct model choice. However, co-culture experiments are far more challenging: we show that these same spatial statistics which provide useful insight into mono-culture systems are insuffcient for co-culture systems. Therefore, we conclude that great care ought to be exercised when estimating the parameters of co-culture assays.

The biology of an isolated population of American Flamingo Phoenicopterus ruber in the Galapagos Islands

A genetically and morphologically divergent population of c.500 American Flamingos, isolated from the parental Caribbean stock of Phoenicopterus ruber, occurs in the Galapagos archipelago. Based primarily on data from a 3-year study, we provide the first description of the feeding and breeding biology of this population. Galapagos provides a suitable habitat comprising lagoons on a number of islands, among which the flamingos travel in response to food and nest site availability. The occurrence and qualnity of some food species was associated with the chlorosity of lagoon water, as was the distribution of flamingos. They bred opportunistically at five lagoons on four islands, sometimes simultaneously on more than one island. Group display usually involved approx 20 birds and colonies contained as few as three nests. Laying occurred during nine months of the year... We review potential dangers to this unique population and suggest conservation measures.

Biology Aotearoa : Unique Flora, Fauna and Fungi

As a large, isolated and relatively ancient landmass, New Zealand occupies a unique place in the biological world, with distinctive terrestrial biota and a high proportion of primitive endemic forms. Biology Aotearoa covers the origins, evolution and conservation of the New Zealand flora, fauna and fungi. Each chapter is written by specialists in the field, often working from different perspectives to build up a comprehensive picture. Topics include: the geological history of our land origins, and evolution of our plants, animals and fungi current status of rare and threatened species past, present and future management of native species the effect of human immigration on the native biota. Colour diagrams and photographs are used throughout the text. This book is suitable for all students of biology or ecology who wish to know about the unique nature of Aotearoa New Zealand and its context in the biological world.

In silico biology : making the most of parallel computing

Biological systems are typically complex and adaptive, involving large numbers of entities, or organisms, and many-layered interactions between these. System behaviour evolves over time, and typically benefits from previous experience by retaining memory of previous events. Given the dynamic nature of these phenomena, it is non-trivial to provide a comprehensive description of complex adaptive systems and, in particular, to define the importance and contribution of low-level unsupervised interactions to the overall evolution process. In this chapter, the authors focus on the application of the agent-based paradigm in the context of the immune response to HIV. Explicit implementation of lymph nodes and the associated lymph network, including lymphatic chain structure, is a key objective, and requires parallelisation of the model. Steps taken towards an optimal communication strategy are detailed.

Complexity and high-end computing in biology and medicine

Biomedical systems involve a large number of entities and intricate interactions between these. Their direct analysis is, therefore, difficult, and it is often necessary to rely on computational models. These models require significant resources and parallel computing solutions. These approaches are particularly suited, given parallel aspects in the nature of biomedical systems. Model hybridisation also permits the integration and simultaneous study of multiple aspects and scales of these systems, thus providing an efficient platform for multidisciplinary research.

From bio-inspired computing to e-Biology

Several algorithms and techniques widely used in Computer Science have been adapted from, or inspired by, known biological phenomena. This is a consequence of the multidisciplinary background of most early computer scientists. The field has now matured, and permits development of tools and collaborative frameworks which play a vital role in advancing current biomedical research. In this paper, we briefly present examples of the former, and elaborate upon two of the latter, applied to immunological modelling and as a new paradigm in gene expression.

Plant biology: Coding in non-coding RNAs

The discovery of peptides encoded by what were thought to be non-coding – or 'junk' – regions of precursors to microRNA sequences reveals a new layer of gene regulation. These sequences may not be junk, after all.

Inventing life: Intellectual property and the new biology

In 2009, the National Research Council of the National Academies released a report on A New Biology for the 21st Century. The council preferred the term ‘New Biology’ to capture the convergence and integration of the various disciplines of biology. The National Research Council stressed: ‘The essence of the New Biology, as defined by the committee, is integration—re-integration of the many sub-disciplines of biology, and the integration into biology of physicists, chemists, computer scientists, engineers, and mathematicians to create a research community with the capacity to tackle a broad range of scientific and societal problems.’ They define the ‘New Biology’ as ‘integrating life science research with physical science, engineering, computational science, and mathematics’. The National Research Council reflected: 'Biology is at a point of inflection. Years of research have generated detailed information about the components of the complex systems that characterize life––genes, cells, organisms, ecosystems––and this knowledge has begun to fuse into greater understanding of how all those components work together as systems. Powerful tools are allowing biologists to probe complex systems in ever greater detail, from molecular events in individual cells to global biogeochemical cycles. Integration within biology and increasingly fruitful collaboration with physical, earth, and computational scientists, mathematicians, and engineers are making it possible to predict and control the activities of biological systems in ever greater detail.' The National Research Council contended that the New Biology could address a number of pressing challenges. First, it stressed that the New Biology could ‘generate food plants to adapt and grow sustainably in changing environments’. Second, the New Biology could ‘understand and sustain ecosystem function and biodiversity in the face of rapid change’. Third, the New Biology could ‘expand sustainable alternatives to fossil fuels’. Moreover, it was hoped that the New Biology could lead to a better understanding of individual health: ‘The New Biology can accelerate fundamental understanding of the systems that underlie health and the development of the tools and technologies that will in turn lead to more efficient approaches to developing therapeutics and enabling individualized, predictive medicine.’ Biological research has certainly been changing direction in response to changing societal problems. Over the last decade, increasing awareness of the impacts of climate change and dwindling supplies of fossil fuels can be seen to have generated investment in fields such as biofuels, climate-ready crops and storage of agricultural genetic resources. In considering biotechnology’s role in the twenty-first century, biological future-predictor Carlson’s firm Biodesic states: ‘The problems the world faces today – ecosystem responses to global warming, geriatric care in the developed world or infectious diseases in the developing world, the efficient production of more goods using less energy and fewer raw materials – all depend on understanding and then applying biology as a technology.’ This collection considers the roles of intellectual property law in regulating emerging technologies in the biological sciences. Stephen Hilgartner comments that patent law plays a significant part in social negotiations about the shape of emerging technological systems or artefacts: 'Emerging technology – especially in such hotbeds of change as the life sciences, information technology, biomedicine, and nanotechnology – became a site of contention where competing groups pursued incompatible normative visions. Indeed, as people recognized that questions about the shape of technological systems were nothing less than questions about the future shape of societies, science and technology achieved central significance in contemporary democracies. In this context, states face ongoing difficulties trying to mediate these tensions and establish mechanisms for addressing problems of representation and participation in the sociopolitical process that shapes emerging technology.' The introduction to the collection will provide a thumbnail, comparative overview of recent developments in intellectual property and biotechnology – as a foundation to the collection. Section I of this introduction considers recent developments in United States patent law, policy and practice with respect to biotechnology – in particular, highlighting the Myriad Genetics dispute and the decision of the Supreme Court of the United States in Bilski v. Kappos. Section II considers the cross-currents in Canadian jurisprudence in intellectual property and biotechnology. Section III surveys developments in the European Union – and the interpretation of the European Biotechnology Directive. Section IV focuses upon Australia and New Zealand, and considers the policy responses to the controversy of Genetic Technologies Limited’s patents in respect of non-coding DNA and genomic mapping. Section V outlines the parts of the collection and the contents of the chapters.

Intellectual property and emerging technologies: The new biology

This unique and comprehensive collection investigates the challenges posed to intellectual property by recent paradigm shifts in biology. It explores the legal ramifications of emerging technologies, such as genomics, synthetic biology, stem cell research, nanotechnology, and biodiscovery. Extensive contributions examine recent controversial court decisions in patent law – such as Bilski v. Kappos, and the litigation over Myriad’s patents in respect of BRCA1 and BRCA2 – while other papers explore sui generis fields, such as access to genetic resources, plant breeders' rights, and traditional knowledge. The collection considers the potential and the risks of the new biology for global challenges – such as access to health-care, the protection of the environment and biodiversity, climate change, and food security. It also considers Big Science projects – such as biobanks, the 1000 Genomes Project, and the Doomsday Vault. The inter-disciplinary research brings together the work of scholars from Australia, Canada, Europe, the UK and the US and involves not only legal analysis of case law and policy developments, but also historical, comparative, sociological, and ethical methodologies. Intellectual Property and Emerging Technologies will appeal to policy-makers, legal practitioners, business managers, inventors, scientists and researchers.

Inventing life: Patent law and synthetic biology

With promises of improved medical treatments, greener energy and even artificial life, the field of synthetic biology has captured the public imagination and attracted significant government and commercial investment. This excitement reached a crescendo on 21 May 2010, when scientists at the J Craig Venter Institute in the United States announced that they had made a “self-replicating synthetic bacterial cell”. This was the first living cell to have an entirely human-made genome, which means that all of the cell’s characteristics were controlled by a DNA sequence designed by scientists. This achievement in biological engineering was made possible by combining molecular biotechnology, gene synthesis technology and information technology.

Genetics of rheumatoid arthritis contributes to biology and drug discovery

A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ~10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2, 3, 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci6 and pathway analyses7, 8, 9—as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes—to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.

Convergence of regenerative medicine and synthetic biology to develop standardized and validated models of human diseases with clinical relevance

In order to progress beyond currently available medical devices and implants, the concept of tissue engineering has moved into the centre of biomedical research worldwide. The aim of this approach is not to replace damaged tissue with an implant or device but rather to prompt the patient's own tissue to enact a regenerative response by using a tissue-engineered construct to assemble new functional and healthy tissue. More recently, it has been suggested that the combination of Synthetic Biology and translational tissue-engineering techniques could enhance the field of personalized medicine, not only from a regenerative medicine perspective, but also to provide frontier technologies for building and transforming the research landscape in the field of in vitro and in vivo disease models.

A Bayesian Framework for the Assessment of Vision-based Weed and Fruit Detection and Classification Algorithms

This paper proposes new metrics and a performance-assessment framework for vision-based weed and fruit detection and classification algorithms. In order to compare algorithms, and make a decision on which one to use fora particular application, it is necessary to take into account that the performance obtained in a series of tests is subject to uncertainty. Such characterisation of uncertainty seems not to be captured by the performance metrics currently reported in the literature. Therefore, we pose the problem as a general problem of scientific inference, which arises out of incomplete information, and propose as a metric of performance the(posterior) predictive probabilities that the algorithms will provide a correct outcome for target and background detection. We detail the framework through which these predicted probabilities can be obtained, which is Bayesian in nature. As an illustration example, we apply the framework to the assessment of performance of four algorithms that could potentially be used in the detection of capsicums (peppers).