Jean-Marc Schwartz

Aug 23, 2024 | nature.com | Jean-Marc Schwartz

AbstractOvarian cancer is an aggressive, heterogeneous disease, burdened with late diagnosis and resistance to chemotherapy. Clinical features of ovarian cancer could be explained by investigating its metabolism, and how the regulation of specific pathways links to individual phenotypes. Ovarian cancer is of particular interest for metabolic research due to its heterogeneous nature, with five distinct subtypes having been identified, each of which may display a unique metabolic signature.

Aug 11, 2024 | nature.com | Tatsuya Akutsu |Jean-Marc Schwartz

AbstractNetwork controllability is unifying the traditional control theory with the structural network information rooted in many large-scale biological systems of interest, from intracellular networks in molecular biology to brain neuronal networks. In controllability approaches, the set of minimum driver nodes is not unique, and critical nodes are the most important control elements because they appear in all possible solution sets.

Jan 19, 2024 | nature.com | Tatsuya Akutsu |Jean-Marc Schwartz |Wataru Someya

AbstractRecent controllability analyses have demonstrated that driver nodes tend to be associated to genes related to important biological functions as well as human diseases. While researchers have focused on identifying critical nodes, intermittent nodes have received much less attention. Here, we propose a new efficient algorithm based on the Hamming distance for computing the importance of intermittent nodes using a Minimum Dominating Set (MDS)-based control model.

Nov 27, 2023 | biorxiv.org | Marcelo Ribeiro-Alves |David Robertson |Jean-Marc Schwartz |Fábio Porto

AbstractIn the battle of the host against lentiviral pathogenesis, the immune response is crucial. However, several questions remain unanswered about the interaction with different viruses and their influence on disease progression. The simian immunodeficiency virus (SIV) infecting nonhuman primates (NHP) is widely used as a model for the study of the human immunodeficiency virus (HIV).

Oct 28, 2023 | biorxiv.org | Soukaina Timouma |Jean-Marc Schwartz |Daniela Delneri

AbstractIn silico tools such as genome-scale metabolic models (GSMM) have shown to be powerful for metabolic engineering of microorganisms. Here, we created the iSP_1513 GSMM for the aneuploid hybrid S. pastorianus CBS1513 to allow top-down computational approaches to predict the evolution of metabolic pathways and to aid strain optimisation and media engineering in production processes.