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7 Investigations visible to you, out of a total of 7

We performed topological analysis on pathways from a harmonised dataset containing pathways from the COVID-19 Disease Map, WikiPathways, and Reactome. The analysis was done using Vanted, SBGN-ED, and LMME which support the import and export of several standard formats (such as SBML, and SBGN-ML).

Multiscale and multicellular simulation of SARS-CoV-2 infection uncover points of intervention to evade apoptosis.


Our framework enables the simulation of the dynamics of signaling pathways that include the relevant players in SARS-CoV-2 infection, at the level of the individual cell and of the cell population. These different players encompass the virus, epithelial and immune cells. The model focuses on apoptosis and suggests two knock out alterations that force apoptosis of the ...

The COVIDminer text mining project ( reads the published literature concerning SARS-CoV-2 and COVID-19 to extract statements about (primarily molecular) interactions. Using the API associated with this project, putative interactors can be automatically retrieved for the existing COVID-19 Disease Maps. New interactions are prioritised based on their frequency in the literature and the topological importance of the interaction targets to provide a focussed set ...

Submitter: Rupert Overall

Studies: No Studies

Assays: No Assays

We further used the transcriptome dataset from the GEO database with accession number GSE147507 (Blanco-Melo et al., 2020) to extract the series number 5 from the dataset, consisting of 2 conditions in triplicate, A549 cells treated with a mock and A549 infected with SARS-CoV-2, measured 24 hours after treatment. Phosphoproteomic data of mock-treated and SARS-CoV2 infected cells were extracted from (Stukalov et al., 2020). We then applied our pipeline described in M&M X. This work notably ...

In this investigation, we aim to develop automatic workflows to pinpoint drug targets carrying genomic variants at high frequency in the population

In this investigation we aim to develop automatic workflows to analyze COVID19 Omics data to understand and predict the molecular pathways depicting host-virus interaction.

We develop macrophage logical models to represent the activation/polarization of this immune cell. Interactions are manually curated with available macrophage literature. The models are mainly built and analyzed in GINsim. But other resources are used to integrate specific pathways or small modules (CasQ software) and to analyze the logical models (CoLoMoTo Notebooks).

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