Océane Cassan

Océane Cassan

Postdoc researcher in statistical learning applied to gene regulation

LIRMM - Laboratory of Computer Science, Robotics and Microelectronics of Montpellier

Biography

I am a postdoc researcher using and developping statistical learning methods to extract knowledge from large biological datasets and decipher the mechanisms behind gene regulation. I completed my PhD in bioinformatics and biostatistics in the Institute for Plant Science of Montpellier, France, where I applied machine learning to genomic data to understand plants responses to climate change. In particular, I modelled the gene regulatory networks in Arabidopsis thaliana under high atmospheric CO2 concentration using regression frameworks in high dimensional settings.

Interests

  • Predictive biology, systems biology
  • Statistical learning
  • Gene regulation

Education

  • PhD in biostatistics for gene regulation - Integrative Biology, Diversity and Plant Improvement, 2022

    University of Montpellier, France

  • MSc in Computer Science - Artificial Intelligence, 2019

    Université Claude Bernard Lyon I, France

  • Engineering degree in Bioinformatics and Modelling, 2019

    National Institute of Applied Sciences (INSA) Lyon, France

Experience

 
 
 
 
 

PhD Student

SIRENE team, BPMP unit, Supagro Montpellier

Oct 2019 – Present Montpellier, France
Statistical inference of the gene regulatory network in Arabidopsis thaliana under climate change. Supervised by Antoine Martin and Sophie Lèbre.
 
 
 
 
 

Research internship

LIRMM - MAB team

Feb 2019 – Aug 2019 Montpellier, France
Machine learning to predict the interactions between chromosomic regions in the human genome, based on CAGE data and 3C techniques
 
 
 
 
 

R&D internship

Nanolive SA

May 2018 – Aug 2016 Lausanne, Switzerland
Development of software tools for the 3D tracking of biological objects in label free images
 
 
 
 
 

Research internship

LIRMM - MAB team

Jul 2017 – Aug 2017 Montpellier, France
Lasso logistic regression models to predict transcription factor binding based on regulatory sequence composition

Skills

Computer science

R programming, Shiny apps, R packages, Rmarkdown, Python, Git, Latex

Data science

Modelling, Statistics, Data visualization

Plant biolgy

Systems biology, Gene Regulatory Networks, quantitative biology

Projects

*

Organisation of the workshop on plants and climate change

Organiser of the international workshop hosted by the BPMP research unit

DIANE

Dashboard for the Inference and Analysis of Networks from Expression data.

AraNetBench

Evaluate the result of a network inference method against known, experimentally determined, regulatory interactions in Arabidopsis thaliana

Master internship project : Statistical learning for the prediction of chromosomic interactions

Statistical learning for the prediction of chromosomic interactions