Name: Systems Biology at University of Michigan
Type: Organization
Bio: Machine learning and constraint-based modeling software from the Chandrasekaran Lab
Twitter: sriram_lab
Location: North Campus Research Complex, Ann Arbor, MI
Blog: https://systemsbiologylab.org/
Systems Biology at University of Michigan's Projects
Using gene expression data to identify regulatory interactions between transcription factors and target genes.
BME499 course materials
Condition-specific Antibiotic Regimen Assessment using Mechanistic Learning
Fitting time-course metabolomics onto genome-scale metabolic models for inferring metabolic activity.
Another tutorial and resource for using docker to launch web applications
epigenome scale metabolic modeling for cancer metabolism
Modeling the metabolic changes during the epithelial-to-mesenchymal transition.
Integrating the transcriptional regulatory network with genome-scale metabolic models.
Another version control resource and tutorial repo
Implementation of INDIGO (INferring Drug Interactions using chemoGenomics and Orthology) as a Python package.
Metabolism And GENomics-based Tailoring of Antibiotic regimens: predicts the impact of pathogen environment on antibiotic potency based on chemogenomic data.
Machine learning to learn metabolite-histone-drug interactions in cancer.
Constraint-based metabolic modeling software from the Chandrasekaran Lab
Common biochemical and topological attributes of metabolic genes recurrently dysregulated in tumors.
A dashboard for the MetOncoFit tumor models.
Leveraging Metabolic Modeling and Machine Learning to Uncover Modulators of Quiescence Depth
Analysis of neutrophil metabolic activity during metastasis using single-cell RNASeq and COnstraint-Based Reconstruction and Analysis.