Thursday 25th November 2021  09.00- CET

Dr. Elva María Novoa del Toro

Postdoc at the French National Research Institute for Agriculture, Food and Environment (INRAE)

Metabolism and Xenobiotics (MeX) / Toxalim / INRAE / Toulouse, France

Detecting Active Modules in Multiplex Biological Networks


One of the most challenging tasks in computational biology is the integration of complementary biological data produced from different experimental sources. Our goal here is to combine expression data and biological networks to identify “active modules”, i.e., subnetworks of interacting genes/proteins associated with expression changes in different biological contexts. We developed MOGAMUN, a multi-objective genetic algorithm that finds dense and overall deregulated subnetworks in a multiplex network. We compared the performance of MOGAMUN with 3 active module identification state-of-the-art methods (jActiveModules (Ideker et al. 2002),COSINE (Ma et al. 2011) and PinnacleZ (Chuang et al. 2007)), on simulated expression datasets, where MOGAMUN showed the best performances. We also applied MOGAMUN to identify active modules for a rare monogenic disease, Facioscapulohumeral muscular dystrophy (FSHD), and for breast cancer. We found active modules representing both known and new altered cellular processes in patients suffering either FSHD or breast cancer. MOGAMUN is available as a Bioconductor package.

Key references:

Ideker, T., Ozier, O., Schwikowski, B., & Siegel, A. F. (2002). Discovering regulatory and signalling circuits in molecular interaction networks. Bioinformatics,18(suppl_1), S233-S240.

Ma, H., Schadt, E. E., Kaplan, L. M., & Zhao, H. (2011). COSINE: COndition-SpecIfic sub-NEtwork identification using a global optimization method. Bioinformatics,27(9), 1290-1298.

Chuang, H. Y., Lee, E., Liu, Y. T., Lee, D., & Ideker, T. (2007). Network based classification of breast cancer ‐ metastasis. Molecular systems biology, 3(1).


Elva María Novoa del Toro is an Engineer in Computer Science (Technological Institute of Cd. Guzmán, Mexico), with a Master’s Degree in Artificial Intelligence (University of Veracruz, Mexico), and a PhD in Bioinformatics (Aix-Marseille University, France). She won the State Award for early research in 2008, and the Art, Science and Light award, to the best receptional thesis of the University of Veracruz in 2015. She started working in the systems biology field in 2017, where she dealt with omics data, in particular, transcriptomics and, more recently, metabolomics. Elva did her PhD at the Marseille Medical Genetics (MMG) lab, and defended in May of 2020. Elva is currently doing a postdoc at the INRAE (French National Research Institute for Agriculture, Food and Environment) where she is working in the integration, analysis and exploration of different types of metabolic networks as a multi-layer network. Her main interest is the use of Artificial Intelligence to solve real-world problems, in particular, those related to health and/or biology.


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