A place to keep things in place.
I am a formally trained biochemist with graduate and post-doctoral work in Computational Systems Biology. Most of my work has been on applications of machine learning tools in biology, with a particular focu for the inference of biologically relevant networks. You can find my CV here.
I currently lead the Machine Intelligence and Data Analytics (MIDAS) lab at the Wyss Institute for Biologically Inspired Engineering. Do not hesitate to reach out to find out about what we are currently working on, new job opportunities, or engage in novel collaborations.
A list of some of my public repositories. Happy to talk to you more about these.
DrugMineR: An R package for querying drugs/compounds in order to extract metadata on these drugs. Data is collated from PubChem and KEGG for now, with expansions coming in the future.
nsmblR: An R package for the inference of ensemble model of gene regulatory networks. For this ensemble I use 7 different inference algorithms that focus on different statistical and mathematical methodologies.
DiffNet: An R package for the identification of topological differences in gene regulatory networks based on a compendium of expression data.
rpegeos: An R package for the enrichment of pathways using natural language processing concepts.
oranges: An R package for the enrichment of pathways using Fisher’s exact test. Limited to human pathways.
These repositories hold data/code for analyses performed on different papers. I include a link to the paper itself for completeness.
Jalili et al., 2019: Analyses of microbiome data in a microfluidic anaerobic chamber. Paper by Jalili et al. [Paper]
Tovaglieri et al., 2018: Computational analyses of metabolomics and 16S data from Organ-Chip samples exposed to enterohemorraghic E. coli. [Paper]