A computational method for quantifying morphological variation in scleractinian corals

Morphological variation in marine sessile organisms is frequently related to environmental factors. Quantifying such variation is relevant in a range of ecological studies. For example, analyzing the growth form of fossil organisms may indicate the state of the physical environment in which the organism lived. A quantitative morphological comparison is important in studies where marine sessile organisms are transplanted from one environment to another. This study presents a method for the quantitative analysis of three-dimensional (3D) images of scleractinian corals obtained with X-ray Computed Tomography scanning techniques. The advantage of Computed Tomography scanning is that a full 3D image of a complex branching object, including internal structures, can be obtained with a very high precision. There are several complications in the analysis of this data set. In the analysis of a complex branching object, landmark-based methods usually do not work and different approaches are required where various artifacts (for example cavities, holes in the skeleton, scanning artifacts, etc.) in the data set have to be removed before the analysis. A method is presented, which is based on the construction of a medial axis and a combination of image-processing techniques for the analysis of a 3D image of a complex branching object where the complications mentioned above can be overcome. The method is tested on a range of 3D images of samples of the branching scleractinian coral Madracis mirabilis collected at different depths. It is demonstrated that the morphological variation of these samples can be quantified, and that biologically relevant morphological characteristics, like branch-spacing and surface/volume ratios, can be computed. Electronic supplementary material The online version of this article (doi:10.1007/s00338-007-0270-6) contains supplementary material, which is available to authorized users

Systems biology: Parameter estimation for biochemical models

Mathematical models of biological processes have various applications: to assist in understanding the functioning of a system, to simulate experiments before actually performing them, to study situations that cannot be dealt with experimentally, etc. Some parameters in the model can be directly obtained from experiments or from the literature. Others have to be inferred by comparing model results to experiments. In this minireview, we discuss the identifiability of models, both intrinsic to the model and taking into account the available data. Furthermore, we give an overview of the most frequently used approaches to search the parameter space

Modelling genetic regulation of growth and form in a branching sponge

We present a mathematical model of the genetic regulation controlling skeletogenesis and the influence of the physical environment on a branching sponge with accretive growth (e.g. Haliclona oculata or Lubomirskia baikalensis). From previous work, it is known that high concentrations of silicate induce spicule formation and upregulate the silicatein gene. The upregulation of this gene activates locally the production of spicules in the sponge and the deposition of the skeleton. Furthermore, it is known that the expression of the gene Iroquois induces the formation of an aquiferous system, consisting of exhalant and inhalant pores. We propose a model of the regulatory network controlling the separation in time and space of the skeletogenesis and the formation of the aquiferous system. The regulatory network is closely linked with environmental influences. In building a skeleton, silicate is absorbed from the environment. In our model, silicate is transported by diffusion through the environment and absorbed at the surface of a geometric model of the sponge, resulting in silicate gradients emerging in the neighbourhood of the sponge. Our model simulations predict sponge morphology and the positioning of the exhalant pores over the surface of the sponge

Kamiya Fuji sensei o shinonde

Morphometrics, the assignment of quantities to biological shapes, is a powerful tool to address taxonomic, evolutionary, functional and developmental questions. We propose a novel method for shape quantification of complex modular architecture in thalloid plants, whose extremely reduced morphologies, combined with the lack of a formal framework for thallus description, have long rendered taxonomic and evolutionary studies extremely challenging.Using graph theory, thalli are described as hierarchical series of nodes and edges, allowing for accurate, homologous and repeatable measurements of widths, lengths and angles.The computer program MorphoSnake was developed to extract the skeleton and contours of a thallus and automatically acquire, at each level of organization, width, length, angle and sinuosity measurements.Through the quantification of leaf architecture in Hymenophyllum ferns (Polypodiopsida) and a fully worked example of integrative taxonomy in the taxonomically challenging thalloid liverwort genus Riccardia, we show that MorphoSnake is applicable to all ramified plants. This new possibility of acquiring large numbers of quantitative traits in plants with complex modular architectures opens new perspectives of applications, from the development of rapid species identification tools to evolutionary analyses of adaptive plasticity.</p