@inproceedings{1a9aee27a51d4424bf74847477a17c86,
title = "Linking genome and exposome: Computational analysis of human variation in chemical-target interactions",
abstract = "The growing amount of available public data repositories containing a plethora of rich chemical and biomedical information is enabling new in silico research avenues. In this project we aim to link human genome variations and the exposome applying in silico biomedical informatics approaches to analyse the potential effects of those variants in the interactions with different chemicals.",
keywords = "Exposome, Protein modelling, Single nucleotide variant, Toxicogenomics, Translational bioinformatics",
author = "Liana Bruggemann and Christopher Hawthorne and Ram Samudrala and Lopez-Campos, \{Guillermo H.\}",
note = "Publisher Copyright: {\textcopyright} 2020 European Federation for Medical Informatics (EFMI) and IOS Press.; 30th Medical Informatics Europe Conference, MIE 2020 ; Conference date: 28-04-2020 Through 01-05-2020",
year = "2020",
month = jun,
day = "16",
doi = "10.3233/SHTI200427",
language = "English",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press",
pages = "1331--1332",
editor = "Pape-Haugaard, \{Louise B.\} and Christian Lovis and Madsen, \{Inge Cort\} and Patrick Weber and Nielsen, \{Per Hostrup\} and Philip Scott",
booktitle = "Digital Personalized Health and Medicine - Proceedings of MIE 2020",
}