Network Biology of Breast Cancer:
High-throughput, multi-omics data of breast cancer can be studied through the use of network approaches. Some of the things me and my colleagues have studied include:
How transcriptional networks capture the heterogeneity of breast cancer molecular subtypes.
Differences in the modular structure of breast cancer networks and subtype-specific functions associated to certain subtypes of breast cancer.
The loss of inter-chromosomal co-expression in breast cancer, and how information-theoretical approaches can be used to study this spatial organization phenomena.
Network-based analysis of pathway deregulation:
The pathways involved in necessary biological functions often exhibit alterations in pathological conditions. We have approached these alterations from a network perspective to study:
Network Pharmacology of Adverse Drug Reactions:
Drugs may act on more than one site inside the organism. Sometimes this leads to adverse drug reactions, which may range from inconvenient to life-threatening. We have used network models to identify:
Metagenomics, Systems Pharmacology and Resistance:
As part of our Cátedra CONACYT project, we are interested in assessing the effects of antibiotic agents in microbial communities, and the way in which these interactions lead to the emergence of resistance.
Other Applications of Network, Data, and Complexity Sciences:
Some other topics that I have been exploring lately include:
- Probabilistic multilayer networks.
- How to appropriately analyze and compare functional enrichment associated to modular structures in biological networks.
- Disease spreading in multilayer networks.
- The evolution of regulations regarding Genetically Modified Organisms in Mexico.
