Abstract : Melanoma is the most lethal type of skin cancer. In this study for the first time we analyze a Greek cohort of primary cutaneous melanoma biopsies, subjected to whole exome sequencing, in order to derive their mutational profile landscape. Moreover, in the context of big data analytical methodologies, we integrated the results of the exome sequencing analysis with transcriptomic data of cutaneous melanoma from GEO, in an attempt to perform a multi-layered analysis and infer a tentative disease network for primary melanoma pathogenesis. The purpose of this research is to incorporate different levels of molecular data, so as to expand our understanding of cutaneous melanoma and the broader molecular network implicated with this type of cancer. Overall, we showed that the results of the integrative analysis offer deeper insight in the underlying mechanisms affected by melanoma and could potentially contribute to the valuable effective epidemiological characterization of this disease.
Lazaros Iliadis; Ilias Maglogiannis. 12th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2016, Thessaloniki, Greece. IFIP Advances in Information and Communication Technology, AICT-475, pp.39-52, 2016, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-319-44944-9_4〉
https://hal.inria.fr/hal-01557640
Contributeur : Hal Ifip
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Soumis le : jeudi 6 juillet 2017 - 13:55:36
Dernière modification le : vendredi 1 décembre 2017 - 01:16:26
Document(s) archivé(s) le : mercredi 24 janvier 2018 - 01:22:55
Georgia Kontogianni, Olga Papadodima, Ilias Maglogiannis, Konstantina Frangia-Tsivou, Aristotelis Chatziioannou. Integrative Bioinformatic Analysis of a Greek Epidemiological Cohort Provides Insight into the Pathogenesis of Primary Cutaneous Melanoma. Lazaros Iliadis; Ilias Maglogiannis. 12th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2016, Thessaloniki, Greece. IFIP Advances in Information and Communication Technology, AICT-475, pp.39-52, 2016, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-319-44944-9_4〉. 〈hal-01557640〉
