1. Gusenleitner, D., Auerbach, S. S., Melia, T., Gómez, H. F., Sherr, D. H. & Monti, S. Genomic models of short-term exposure accurately predict long-term chemical carcinogenicity and identify putative mechanisms of action. PLoS One 9, e102579 (2014). PMID: 25058030

  2. Mulas, F., Li, A., Sherr, D. H. & Monti, S. Network-based analysis of transcriptional profiles from chemical perturbations experiments. BMC Bioinformatics 18, 130 (2017). PMID: 28361664

  3. Li, A., Lu, X., Natoli, T., Bittker, J., Sipes, N. S., Subramanian, A., Auerbach, S., Sherr, D. H. & Monti, S. The Carcinogenome Project: In Vitro Gene Expression Profiling of Chemical Perturbations to Predict Long-Term Carcinogenicity. Environ. Health Perspect. 127, 47002 (2019). PMID: 30964323

  4. Kim, S., Li, A., Monti, S. & Schlezinger, J. J. Tributyltin induces a transcriptional response without a brite adipocyte signature in adipocyte models. Arch. Toxicol. 92, 2859–2874 (2018). PMID: 30027469

  5. Kim, S., Reed, E., Monti, S. & Schlezinger, J. A Data-Driven Transcriptional Taxonomy of Adipogenic Chemicals to Identify White and Brite Adipogens. bioRxiv 519629, Under 2nd review at Env. Health Persp. (2019).

  6. Reed, E. R. & Monti, S. Multi-resolution characterization of molecular taxonomies in bulk and single-cell transcriptomics data. bioRxiv 2020.11.05.370197 (2020). doi:10.1101/2020.11.05.370197