Selected Publications

SYSTEMS TOXICOLOGY

Kinaret P, et al. Network Analysis Reveals Similar Transcriptomic Responses to Intrinsic Properties of Carbon Nanomaterials in Vitro and in Vivo. ACS Nano. 2017 Apr 25;11(4):3786-3796. doi: 10.1021/acsnano.6b08650.

Kinaret P, et al. Inhalation and Oropharyngeal Aspiration Exposure to Rod-Like Carbon Nanotubes Induce Similar Airway Inflammation and Biological Responses in Mouse Lungs. ACS Nano. 2017 Jan 24;11(1):291-303. doi: 10.1021/acsnano.6b05652.

Rydman EM, et al. A Single Aspiration of Rod-like Carbon Nanotubes Induces Asbestos-like Pulmonary Inflammation Mediated in Part by the IL-1 Receptor. Toxicol Sci. 2015 Sep;147(1):140-55.

Palomäki J, et al. A secretomics analysis reveals major differences in the macrophage responses towards different types of carbon nanotubes. Nanotoxicology. 2014 Oct 17:1-10.

Rydman EM, et al. Inhalation of Rod-Like Carbon Nanotubes Causes Unconventional Allergic Airway Inflammation. Part Fibre Toxicol. 2014 Oct 16;11:48.

Napolitano F, et al. Drug repositioning: a machine-learning approach through data integration. J Cheminform. 2013 Jun 22;5(1):30. doi: 10.1186/1758-2946-5-30.

BIOINFORMATICS

Marwah VS, et al. INfORM: Inference of NetwOrk Response Modules. Bioinformatics. 2018 Feb 7.

Gualdi P, et al. Effectiveness of Projection Techniques in Genomic Data Analysis. IEEE RTSI 2016.

Serra A, et al. Data integration in genomics and systems biology. IEEE CEC 2016 (Review).

Fortino V, et al. CONDOP: an R package for CONdition-Dependent Operon Predictions. Bioinformatics. 2016 Oct 15;32(20):3199-3200. Epub 2016 Jun 13.

Fortino V, et al. BACA: bubble chArt to compare annotations. BMC Bioinformatics. 2015 Feb 5;16(1):37.

Fortino V, et al. A robust and accurate method for feature selection and prioritization from multi-class OMICs data. PLoS One. 2014 Sep 23;9(9):e107801

Molecular Epidemiology

Xu CJ, et al., DNA methylation in childhood asthma: an epigenome-wide meta-analysis. Lancet Respir Med. 2018 Feb 26. pii: S2213-2600(18)30052-3.

Stringhini S, et al. Socioeconomic status and the 25 × 25 risk factors as determinants of premature mortality: a multicohort study and meta-analysis of 1·7 million men and women. Lancet. 2017 Mar 25;389(10075):1229-1237. doi: 10.1016/S0140-6736(16)32380-7. Epub 2017 Feb 1.

Garcia-Closas M, et al. Genome-wide association studies identify four ER negative-specific breast cancer risk loci. Nat Genet. 2013 Apr;45(4):392-8.