Hub members Have many expertise, covering most of the fields in bioinformatics and biostatistics. You'll find below a non-exhaustive list of these expertise
Searched keyword : Fly
Related people (2)
I have a joint MSc degree in Mathematical Modelling from three European universities: University of L’Aquila (Italy), University of Nice-Sophia Antipolis (France) and Autonomous University of Barcelona (Spain). I also hold a PhD degree in Applied Mathematics and Scientific Computing from University of Bordeaux, France. I have done my PhD and one year of post-doc at INRIA Bordeaux Sud-Ouest, and partially at IHU-Liryc. During this time I studied how electrical signals propagate through the cardiac tissue under certain diseased conditions. My model of interest was the bidomain model, which is a system of partial differential equations that takes into account physiological properties of the cardiac cells and the spatial organization of the cardiac tissue. I worked on the mathematical multiscale analysis and numerical simulations of the problem to understand how structural changes of the tissue affect the propagation of the signal on the heart level. I collaborated with biologists and engineers of the IHU-Liryc to apply my model on a rat heart using high-resolution MRI data. For this I also worked on image analysis and image processing. I’ve joined the Institute Pasteur in February 2018 as a member of the HUB in Bioinformatics and Biostatistics. Currently I am working on stochastic mathematical modeling and inference for systems biology, gene expression, RNA transcription, etc.
ModelingScientific computingApplication of mathematics in sciencesGraphics and Image Processing
BacteriaFungiInsect or arthropodEscherichia coliSaccharomyces cerevisiaeFly
- Modelization of the timing of abscission(Arnaud ECHARD - Membrane Traffic and Cell Division) - In Progress
- Estimation of the impact of differential apoptotic rate on local clone size(Romain LEVAYER - Cell death and epithelial homeostasis) - In Progress
- State and parameter inference for stochastic models of gene expression(Jakob RUESS - Other) - Closed
I obtained a PhD in phylogeny in 2008 at the Muséum National d’Histoire Naturelle in Paris, then worked as a post-doc in Torino (Italy, 2009 – 2011) and Faro (Portugal, 2011 – 2013) where I worked on methodological aspects of phylogeny. In 2013, I have been hired as research engineer in bioinformatics at the Institut de Génétique Humaine in Montpellier where I wrote tools to analyse high-throughput sequencing data, especially small RNA-seq. This is also the kind of job I do now at Institut Pasteur, since 2016. I enjoy programming in Python, I’m interested in evolutionary biology, and I find teaching the UNIX command-line and other practical computer skills a rewarding activity. I’m also particularly involved in a course introducing PhD students (and sometimes other staff at Institut Pasteur) to R programming and basic descriptive statistics. The course support is available on-line and can hopefully be studied autonomously: https://hub-courses.pages.pasteur.fr/R_pasteur_phd/First_steps_RStudio.html One of my main activities is the development of automated data analysis workflows using Snakemake. My published work is available here: http://www.normalesup.org/~bli/useful.html
GenomicsNon coding RNATranscriptomicsSofware development and engineeringGeneticsWorkflow and pipeline development
Insect or arthropodOther animalDrosophila melanogaster (Fruit fly)C. elegans
- Codon Usage Bias Analysis in Vibrio(Marie-Eve KENNEDY-VAL - Bacterial Genome Plasticity) - In Progress
- Gene conversion and allelic selection drives L. donovani genomic adaptation in experimental Sand fly infection(Gerald SPAETH - Molecular Parasitology and Signaling) - In Progress
- The LeiSHield-MATI consortium: Investigating genomic adaptation of Leishmania parasites in endemic areas(Gerald SPAETH - Molecular Parasitology and Signaling) - In Progress
Related projects (4)
In early development, regulation of transcription results in precisely positioned and highly reproducible expression patterns that specify cellular identities. How transcription, a fundamentally noisy molecular process, is regulated to achieve reliable embryonic patterning remains unclear. In particular, it is unknown how gene-specific regulation mechanisms affect kinetic rates of transcription, and whether there are common, global features that govern these rates across a genetic network. Quantitative measurements of nascent transcriptional activity in both living and fixed tissues are key in order to understand the underlying transcription kinetics and to make progress with these fundamental questions. The current project aims at constructing realistic minimalist models of transcription for different experimental and developmental contexts, using spatiotemporal gene expression activity data obtained from microscopic imaging of live biological tissues.
We have performed a systemic characterisation of apoptosis distribution and clone dynamics in the Drosophila wing imaginal disc. Surprisingly, we outlined a systematic spatial bias in the rate of apoptosis with regions shoing high rates of apoptosis which correlate with high probability of clone disappearance and small clone size. We would like to formulate analytically the prediction of local clone size assuming a homogenous proliferation rate and knowing spatial differences in clone disappearance probability. This will help to evaluate how much the spatial differences in apoptic rates are sufficient to explain the differences in local growth.
Transcriptional analysis of niche cells in the context of tumour progression in the Drosophila brain
We are interested in the behaviour of healthy cells in the context of tumour growth in the Drosophila brain We want to know the genes changing in healthy cells response to the tumour.
Several molecular pathways are known to play pivotal roles in Drosophila antiviral defense. The main parameters used to assess this response are fly survival and viral titers, which are both helpful to describe pathogenesis and virulence. However, little is known about the processes that prevent infection and if the known antiviral pathways are involved. Moreover, studies of the insect antiviral response are based on the administration of large doses of pathogens that barely simulate the physiology of viral transmission in nature. This may hide the pivotal role of several proteins or molecular processes in conferring resistance against contagion. The aim of our project is to shed light on the role of the known antiviral processes during the initial infection steps. That will be achieved through the development of a novel viral transmission protocol that will help uncover new immunological effectors that prevent viral transmission and infection.