Background and activities
Representation and extraction of causal statements from prior-knowledge.
In systems biology, regulatory process networks are built to depict how components in cell fate decision systems are interconnected and behave. A considerable amount of knowledge provided by different public resources is already available in the form of large biological networks. My project explores this information by breaking down those networks into causal statements: a source entity that influences the activity or the quantity of a target entity given a specific context.
The DrugLogics project is a systems medicine approach to employ computational methods for predicting drug resistance in cancer treatment. The long-term goal is to economize drug screens and to find tailor-made treatments for patients with specific types of cancer. Currently, our pipeline automatically generates boolean models from causal statements to predict drug targets and drug synergies. The extraction of causal statements from existing network resources will feed our model building software pipeline with more input data.
We will design a format to standardize the representation of causal statements by using generally accepted identifiers and ontology terms (i.e. ontology for causal interaction). Using this representation we will design and build software pipelines to extract causal statements from a variety of existing network resources and make them publicly available.
Sep 2015 - Jan 2017 Scientific staff member, Rostock University (Rostock, Germany).
Feb 2015 - Aug 2015 Master internship, European Institute for Systems Biology & Medicine (Lyon, France).
2013 - 2015 MSc in Bioinformatics and Biostatistics, Paris-Sud XI University (Paris, France).
2011 - 2013 BSc in Life Sciences, Pierre et Marie Curie University (Paris, France).
2009 - 2011 Medical Studies, Pierre et Marie Curie University (Paris, France).
Scientific, academic and artistic work
Displaying a selection of activities. See all publications in the database
- (2020) Setting the basis of best practices and standards for curation and annotation of logical models in biology—highlights of the [BC]2 2019 CoLoMoTo/SysMod Workshop. Briefings in Bioinformatics.
- (2020) The Minimum Information about a Molecular Interaction Causal Statement (MI2CAST). Bioinformatics.
- (2019) Harmonizing semantic annotations for computational models in biology. Briefings in Bioinformatics. vol. 20 (2).
- (2019) CausalTAB: the PSI-MITAB 2.8 updated format for signalling data representation and dissemination. Bioinformatics. vol. 35 (19).
- (2019) Systems Biology Graphical Notation: Process Description language Level 1 Version 2.0. Journal of Integrative Bioinformatics (JIB). vol. 16 (2).
- (2019) VSM-box: the general-purpose curation interface as an open-source web-component [version 1; not peer reviewed]. F1000Research 2019, 8:442 (poster). The 12th International Biocuration Conference 2019 ; 2019-04-12.
- (2018) Evolution of computational models in BioModels Database and the Physiome Model Repository. BMC Systems Biology. vol. 12 (1).
- (2018) Quick tips for creating effective and impactful biological pathways using the Systems Biology Graphical Notation. PLoS Computational Biology. vol. 14:e1005740 (2).