@article {711, title = {Mechanistic modeling of the SARS-CoV-2 disease map.}, journal = {BioData Min}, volume = {14}, year = {2021}, month = {2021 Jan 21}, pages = {5}, abstract = {

Here we present a web interface that implements a comprehensive mechanistic model of the SARS-CoV-2 disease map. In this framework, the detailed activity of the human signaling circuits related to the viral infection, covering from the entry and replication mechanisms to the downstream consequences as inflammation and antigenic response, can be inferred from gene expression experiments. Moreover, the effect of potential interventions, such as knock-downs, or drug effects (currently the system models the effect of more than 8000 DrugBank drugs) can be studied. This freely available tool not only provides an unprecedentedly detailed view of the mechanisms of viral invasion and the consequences in the cell but has also the potential of becoming an invaluable asset in the search for efficient antiviral treatments.

}, issn = {1756-0381}, doi = {10.1186/s13040-021-00234-1}, author = {Rian, Kinza and Esteban-Medina, Marina and Hidalgo, Marta R and Cubuk, Cankut and Falco, Matias M and Loucera, Carlos and Gunyel, Devrim and Ostaszewski, Marek and Pe{\~n}a-Chilet, Maria and Dopazo, Joaquin} } @article {702, title = {Mechanistic models of signaling pathways deconvolute the glioblastoma single-cell functional landscapeAbstract}, journal = {NAR Cancer}, volume = {2}, year = {2020}, month = {Jan-06-2020}, doi = {10.1093/narcan/zcaa011}, url = {https://academic.oup.com/narcancer/article/doi/10.1093/narcan/zcaa011/5862620http://academic.oup.com/narcancer/article-pdf/2/2/zcaa011/33428092/zcaa011.pdfhttp://academic.oup.com/narcancer/article-pdf/2/2/zcaa011/33428092/zcaa011.pdf}, author = {Falco, Matias M and Pe{\~n}a-Chilet, Maria and Loucera, Carlos and Hidalgo, Marta R and Dopazo, Joaquin} } @article {404, title = {Models of cell signaling uncover molecular mechanisms of high-risk neuroblastoma and predict disease outcome.}, journal = {Biol Direct}, volume = {13}, year = {2018}, month = {2018 08 22}, pages = {16}, abstract = {

BACKGROUND: Despite the progress in neuroblastoma therapies the mortality of high-risk patients is still high (40-50\%) and the molecular basis of the disease remains poorly known. Recently, a mathematical model was used to demonstrate that the network regulating stress signaling by the c-Jun N-terminal kinase pathway played a crucial role in survival of patients with neuroblastoma irrespective of their MYCN amplification status. This demonstrates the enormous potential of computational models of biological modules for the discovery of underlying molecular mechanisms of diseases.

RESULTS: Since signaling is known to be highly relevant in cancer, we have used a computational model of the whole cell signaling network to understand the molecular determinants of bad prognostic in neuroblastoma. Our model produced a comprehensive view of the molecular mechanisms of neuroblastoma tumorigenesis and progression.

CONCLUSION: We have also shown how the activity of signaling circuits can be considered a reliable model-based prognostic biomarker.

REVIEWERS: This article was reviewed by Tim Beissbarth, Wenzhong Xiao and Joanna Polanska. For the full reviews, please go to the Reviewers{\textquoteright} comments section.

}, keywords = {Computational Biology, Gene Expression Regulation, Neoplastic, Humans, JNK Mitogen-Activated Protein Kinases, Models, Theoretical, Neuroblastoma, Signal Transduction}, issn = {1745-6150}, doi = {10.1186/s13062-018-0219-4}, author = {Hidalgo, Marta R and Amadoz, Alicia and Cubuk, Cankut and Carbonell-Caballero, Jos{\'e} and Dopazo, Joaquin} }