As we are interested to decipher processes generating biological complexity and diversity, our research at the LANE is positioned at the interfaces among molecular developmental biology, mathematical modelling and physics of biology. In the wet lab, we adapt existing techniques (and sometimes develop new approaches) to the particularities of the non-classical model species we work on (see below). Besides using basic molecular biology approaches, we have established successful protocols for whole-mount in-situ hybridisation (fluorescent and chromogenic detection), RT-qPCR, primary cell cultures, ex-vivo tissue cultures, in-ovo drug injections, tissue nanoindentation and histological analyses (paraffin and cryosections, immunohistochemistry, laser capture microdissection). We employ a series of state-of-the-art imaging methods such as bright-field multi-focus imaging, hyperspectral microscopy, fluorescence microscopy, confocal and light-sheet microscopy, scanning and transmission electron microscopy, X-ray and computerised tomography (CT). We also perform 3D surface scanning of skin geometry with structured light as well as with an in-house developed robotic system (R2OBBIE, see below) implementing structure-from-motion and photometric stereo approaches. Most equipments are available in our own lab, in the Genetics & Evolution department or at Bioimaging Centres on campus or at the close-by medical school and hospital.
Our animal models
To be written
R2OBBIE-the-robot is an in-house-developed fast robotic high-resolution system for quantitative phenotyping of surface geometry and colour-texture. R2OBBIE allows us to generate coloured 3D models with a spatial resolution down to 30 microns (!). See the video below and check the article for much additional information.
R2OBBIE-3D, a Fast Robotic High-Resolution System for Quantitative Phenotyping of Surface Geometry and Colour-Texture
Martins A., Bessant M., Manukyan L., M.C. Milinkovitch
PLOS ONE 10, 6 : e0126740 (2015)
MetaPIGA is a versatile and easy-to-use software that implements robust stochastic heuristics (including the Metapopulation Genetic Algorithm, metaGA) for large phylogeny inference under maximum likelihood. MetaPIGA allows analyses of binary and molecular data sets under multiple substitution models, Gamma rate heterogeneity, and data partitioning. The software is for all types of users as it can be run through an extensive and ergonomic graphical interface, or by using batch ﬁles and console interface on your local machine or on distant servers. MetaPIGA is platform independent, and easily takes advantage of GPU and multicore computing.
A JAVA application developed to facilitate the annotation of de novo sequenced transcriptomes. It was extensively used for the Reptilian Brain Transcriptome project (Tzika et al.2011) and for building the subsequent Reptilian Transcriptomes 2.0 database (Tzika et al. 2015).
Softwares for students