Simple guide to starting a research group

Conducting cutting-edge research and scholarship becomes more complicated with each passing year; forming a collaborative research group offers a way to navigate this increasing complexity. Yet many individuals whose work might benefit from the formation of a collaborative team may feel overwhelmed by the prospect of attempting to build and maintain a research group. We propose this simple guide for starting and maintaining such an enterprise

A mechanistic spatio-temporal framework for modelling individual-to-individual transmission—With an application to the 2014-2015 West Africa Ebola outbreak

In recent years there has been growing availability of individual-level spatio-temporal disease data, particularly due to the use of modern communicating devices with GPS tracking functionality. These detailed data have been proven useful for inferring disease transmission to a more refined level than previously. However, there remains a lack of statistically sound frameworks to model the underlying transmission dynamic in a mechanistic manner. Such a development is particularly crucial for enabling a general epidemic predictive framework at the individual level. In this paper we propose a new statistical framework for mechanistically modelling individual-to-individual disease transmission in a landscape with heterogeneous population density. Our methodology is first tested using simulated datasets, validating our inferential machinery. The methodology is subsequently applied to data that describes a regional Ebola outbreak in Western Africa (2014-2015). Our results show that the methods are able to obtain estimates of key epidemiological parameters that are broadly consistent with the literature, while revealing a significantly shorter distance of transmission. More importantly, in contrast to existing approaches, we are able to perform a more general model prediction that takes into account the susceptible population. Finally, our results show that, given reasonable scenarios, the framework can be an effective surrogate for susceptible-explicit individual models which are often computationally challenging

The Use of Natural Kinds in Evolutionary Developmental Biology

Evolutionary developmental biologists categorize many different kinds of things, from ontogenetic stages to modules of gene activity. The process of categorization—the establishment of “kinds”—is an implicit part of describing the natural world in consistent, useful ways, and has an essentially practical rather than philosophical basis. Kinds commonly serve one of three purposes: they may function (1) as practical tools for communication; (2) to support prediction and generalization; or (3) as a basis for theoretical discussions. Beyond the minimal requirement that classifications reflect biological reality, what sorts of kinds or classification will be useful in advancing a research program depends on the epistemological context. Thus, the important meaning of “natural” in “natural kinds” is not “natural with respect to nature,” but “natural with respect to the question.” This conclusion arises from the recognition that the proper role of concepts (e.g. natural kind, module, homology, model) is not to answer biological questions, but rather to help frame them. From a scientist’s perspective, arguing about the wording (or existence) of a single definition of “natural” or “kind” is beside the point: we get more work done by letting the question at hand determine what kinds of kinds are natural, on the basis of their ability to help answer it. We should be content to let “natural kinds” remain vague, multivalent, and–therefore broadly useful. For a philosopher like Hacking, the diverse, disparate, and ultimately incommensurable uses of the term “natural kind” have diluted its value so far that it loses all meaning. For practicing scientists, however, defining useful kinds in the context of particular questions and systems remains a productive epistemological strateg

Modularity in Development and Why It Matters to Evo-Devo

The concept of modularity is fundamental to research in both evolutionary and developmental biology, though workers in each field use the idea in different ways. Although readily and intuitively recognized, modularity is difficult to define precisely. Most definitions of modularity are operational and implicit, particularly in developmental biology. Examination of several proposed definitions points to some general characteristics of developmental modules, for example their internal integration, and suggests the importance of devising a definition applicable at different levels of the biological hierarchy. Modules, like homologs, must be defined with respect to a specified level of the hierarchy, and a general definition should support both analyses of the evolving causal relationships between levels, and studies of the interconnections between modules of the same type. The designation of a developmental structure, process, or function as a “module” is a testable hypothesis; this hypothesis is confirmed in the case of the dorsal marginal zone of the amphibian gastrula, which acts as a morphogenetic module. Discussions of developmental modularity can provide a meeting place for developmental and evolutionary biologists by helping us articulate key questions at the intersection of the two fields, and design experiments to begin answering them

Exemplary and Surrogate Models: Two modes of representation in biology

Biologists use models in two distinct ways that have not been clearly articulated. A model may be used either as an exemplar of a larger group, or as a surrogate for a specific target. Zebrafish serve as an exemplary model of vertebrates in developmental biology; rodents are both exemplary vertebrates and specific surrogates for humans in biomedical research. The distinction between exemplary and surrogate models is important, because the criteria for and implications of model choice diverge in significant ways, depending on which role the model is to serve. So, too, do the kinds of conclusions we can legitimately draw from model-based research. The divergence derives in part from the use of the two sorts of models to answer different kinds of questions: exemplary models most often serve basic research, while surrogate models are used when the target species we ultimately want to learn about is inaccessible or difficult to study, as in medical research. There are many reasons to consider exemplary and surrogate models separately: they are suited to different tasks and contexts, rest on different assumptions, and, finally, they have unique limitations

Models in context: biological and epistemological niches

A model organism’s value depends on its biological and epistemological contexts. The biological context of a model species comprises all aspects of its environment in the research setting that may influence its biological characteristics. In contrast, the epistemological context is not a matter of the organism’s surroundings, but rather of what question it is supposed to help answer, and the assumptions about its “representativeness” that warrant broader application of results from a unique model. The biological context for model organisms in research is highly controlled and standardized. This strategy has often been productive; however, it risks eliminating essential environmental information and biological mechanisms, including organism-environment interactions that help shape phenotypes. Considering biological context helps us avoid experimental designs that simplify potentially important dimensions out of existence. Clarifying the epistemological context, from background assumptions to the ultimate goal of the research, lets us assess how the research approach we choose—such as employing a particular model—may constrain the range or utility of possible answers. Looking at models in context can enrich understanding of both the history and the practice of biology: how models are selected and evolve to fit questions, and how they in turn influence the direction of future work

What\u27s new: the source and uses of homology. [Review]

Review of: What\u27s new: the source and uses of homology Review of G.P. Wagner: Homology, Genes, and Evolutionary Innovation; Princeton University Press, 2014 The concept of homology has a long history and a long bibliography, to which Günter Wagner\u27s book Homology, genes, and evolutionary innovation (Princeton University Press, 2014) represents a significant addition. The volume is an intellectual analog of the morphological innovations it describes: firmly rooted in the past, yet expanding into new intellectual territory, just as a morphological novelty presents new evolutionary possibilitie

From Embryology to Evo-Devo: A History of Developmental Evolution [Review]

Review of: From Embryology to Evo-Devo: A History of Developmental Evolution. Manfred D. Laubichler and Jane Maienschein, eds. MIT Press, Cambridge, MA, 2007. 577 pp., illus. $55.00 (ISBN 9780262122832 cloth). From Embryology to Evo-Devo originated in a 2001 Dibner Institute workshop organized by the book\u27s editors. Manfred D. Laubichler is an assistant professor of biology and an affiliated assistant professor of philosophy at Arizona State University; Jane Maienschein is Regents\u27 Professor and Parents Association Professor at the same university, where she also directs the Center for Biology and Society. Both are long-time observers of, as well as participants in, the modern emergence of evolutionary developmental biology, or “evo-devo.” As they note in the introduction, we continue to confront “a rather old cluster of scientific problems of embryos, development and evolution,” and struggle with how to think about them and what to do about them in the lab. The quest to articulate how ontogeny and phylogeny fit together, and to achieve some kind of conceptual continuity that unifies their disparate timescales and explanatory modes, is a long-standing one. This volume, an anthology of essays, combines a history of these efforts with attempts to move the project forward