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Camille Juigné

I am a PhD student in bioinformatics at both INRAE and IRISA, supervised by Florence Gondret and Emmanuelle Becker.

My research subject concerns the integration and analysis of heterogeneous biological data modelled with multiplex graphs applied to understand and predict variations in feeding efficiency. The objective is to identify networks of molecules to explain an animal phenotype, by considering different levels of organization of the living, using statistics and then by analyzing multilayer graphs. This second approach has the advantage of adopting a holistic view on biological organization by integrating different omic levels. This allows to get closer to reality by considering things as a whole and linked together.

In this case of application, understanding the valorization of food resources by the animal will lead to a saving of resources and a reduction of discharges and effluents into the environment.



2020 - 2023 : PhD in bioinformatics

“Analysis of heterogeneous biological data modelled with multiplex graphs and applied for a better understanding of variations in feed efficiency of growing pigs” at INRAE UMR PEGASE (Physiology, Environment and Genetics for Animals and Breeding Systems) and IRISA in Team Dyliss (DYnamics, Logics and Inference for biological Systems and Sequences)

2016 – 2019 : Advanced National College of Applied Science and Technology (Enssat Lannion)

Diplôme d’ingénieur in Computer Science, Machine Learning, Graph Theory, Software development, Web development, Object Oriented development, Probabilities and Statistics, Project Management
The “Software and Computing” specialised course is a very complete training in computer science. It offers a strong skillsets in the fields of software engineering (methods, algorithms, languages and tools), communication systems, man-to-machine interactivity and data management (data mining, Big Data, artificial intelligence).

Activities and associations :

2018 - 2019 : Université du Québec à Montréal (UQAM)

Master in Computer Science, Machine Learning, Data Mining, Big Data, Intelligent Tutoring System (ITS) and Bioinformatics

2014 - 2016 : Montesquieu high school Le Mans

Preparatory classes for engineering schools, bachelor’s degree in Mathematics, Physics, Engineering and Computer Science


I was in charge of developping interoperable genomic analysis tools for the European Commission : the European Open Science Cloud (EOSC) Life WP2.

Protein–protein interactions are essential to ensure biologic processes, analysing them and considering the cells as an inner system provide us to understand these related processes.The biggest challenge is to discover all these interactions. Until recently, large scale sieve have been made using different methods. However, each one of these methods has its flaws and introduce detection bias. That is why we have been studying new methods to detect these interactions and that we have been extracting all the possible protein-protein interactions of the ubiquitine system in order to analyse them using formal methods. The ubiquitin system governs the stability, activity and abundance of proteins in cells. Aberrations in the ubiquitin system may be linked to multiple pathologies and are particularly involved in human diseases such as cancer and neurodegenerative disorders.




Other talks



2021-today Reading Circle

member of the organization team of the 4th, 5th and 6th edition, participant since the 3rd edition
A reading circle for young researchers (PhD students and Postdocs) to read books on feminist topics within Computer Science together and share our thoughts and experiences.

2021-today Gender Equality Commission

2021 “Elles codent, elles créent”

oct-dec 2021 & feb-may 2021
Computer science and Python initiation for middle school girls (Introduction to computational thinking through creative programming).

2020 COVID19 Virtual BioHackathon 2020

(todo) Transpose Galaxy workflows in CWL :

2018 Ada Lovelace Challenge

Mentor in a team programming competition for high school girls. Students develop web micro-services around a theme chosen by a jury of computer scientists.

2017 Smart-Agri Challenge

Challenge on the theme “Digital technology serves Agriculture”, an experience of entrepreneurship training (working in a project team, being creative, testing, experimenting, being coached by professionals, confronting the field). The objective is to imagine an innovative solution, including digital, for business needs in agriculture.