By this analysis, we have identified 4 genes that were subjected to copy number alterations in tumors arising in all colon segments (defined “common genes”) and the presence of copy number alterations in 14 genes that were significantly associated to one specific site (defined “site-associated genes”). Validation of results was performed on 20 representative genes by quantitative qPCR and/or immunostaining. Overall, we have found a total of 748 significant copy number alterations in 230 significant genes, of which 143 showed CN losses and 87 showed CN gains. We report the successful detection of somatic changes in gene copy number in 37 colon cancer patients by analysis of sequencing data through Amplicon CNA Algorithm. Universita degli Studi 'Magna Græcia' di Catanzaro Department of Health Sciences Catanzaro, Italy Position Professor (Associate) Show All Education November 1997 - February 2001 Università. The objective of this study was to determine the feasibility to detect copy number alterations in colon cancer samples using Next Generation Sequencing data and to elucidate the association between copy number alterations in specific genes and the development of cancer in different colon segments.
It was founded in 1998 and is organized in three faculties. Received: ApAccepted: FebruPublished: April 17, 2018 The Magna Grcia University of Catanzaro ( Italian: Universit degli studi Magna Grcia di Catanzaro) is a university located in Catanzaro, Italy. Keywords: colon cancer Next generation sequencing copy number alteration Cartello 'Mater Domini' - Università degli Studi Magna Græcia di Catanzaro.jpg 1,342 × 1,418 1.16 MB. Giuseppe Viglietto, email: ĭonatella Malanga, email: The following 5 files are in this category, out of 5 total. *These authors contributed equally to this work To apply for this position, or for any additional information, email to deadline for applications is March 10th.Duarte Mendes Oliveira 1, *, Gianluca Santamaria 1, *, Carmelo Laudanna 1, Simona Migliozzi 1, Pietro Zoppoli 1, Michael Quist 4, Catie Grasso 5, Chiara Mignogna 2, Laura Elia 3, Maria Concetta Faniello 1, Cinzia Marinaro 1, Rosario Sacco 3, Francesco Corcione 6, Giuseppe Viglietto 1, Donatella Malanga 1 and Antonia Rizzuto 3ġDipartimento di Medicina Sperimentale e Clinica, Università Magna Graecia, Catanzaro, ItalyĢDipartimento di Scienze della Salute, Università Magna Graecia, Catanzaro, ItalyģDipartimento di Scienze Mediche e Chirurgiche, Università Magna Graecia, Catanzaro, ItalyĤFred Hutchinson Cancer Research Center, Seattle, WA, USAĥUniversity of California Los Angeles (UCLA), Los Angeles, CA, USAĦUOC Chirurgia Generale, Azienda Ospedaliera dei Colli, Napoli, Italy No tenure-track academic position is linked to this job offer. We offer flexible working time and a combination of local/remote working schemes. Payscale at postdoc level depending on the candidate’s experience. Proved publication track record (minimum Scopus H-index equal to 7).PhD in Biomedical Engineering, Computer Science, Computer Vision, Data Science, Medical Physics, or related field, with emphasis on medical image analysis and artificial intelligence (both machine learning and deep learning).The project, in collaboration with the European Institute of Oncology (Milan) and Azienda Ospedaliero-Universitaria Cagliari, aims at using CT scans and artificial intelligence to predict the therapeutic outcomes (both pharmacological and surgical) for gynecological cancer patients. We are looking for a motivated person to work as a post-doc on a medical image analysis project at Magna Graecia University of Catanzaro, Italy.
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