Dr Nicos Angelopoulos

2020

• Rustad, E. H.et al. 2020. Revealing the impact of structural variants in multiple myeloma. Blood Cancer Discovery (10.1158/2643-3230.BCD-20-0132)
• Rustad, E. H.et al. 2020. Timing the initiation of multiple myeloma. Nature Communications 11(1), article number: 1917. (10.1038/s41467-020-15740-9)
• Jones, S.et al. 2020. Targeting of EGFR by a combination of antibodies mediates unconventional EGFR trafficking and degradation. Scientific Reports 10(1), article number: 663. (10.1038/s41598-019-57153-9)
• Draaisma, K.et al. 2020. Molecular evolution of IDH wild-type glioblastomas treated with standard of care affects survival and design of precision medicine trials: a report from the EORTC 1542 study. Journal of Clinical Oncology 38(1), pp. 81-99. (10.1200/JCO.19.00367)

2019

• Maura, F.et al. 2019. Timing the initiation of multiple myeloma. Presented at: 61st American Society of Hematology Annual Meeting, Orlando, FL, USA, 7-10 December 2019, Vol. 134. Vol. Supple. American Society of Hematology, (10.1182/blood-2019-124357)
• Maura, F.et al. 2019. Timing the initiation of multiple myeloma. Presented at: 17th International Myeloma Workshop, Boston, MA, USA, 12-15 September 2019, Vol. 19. Vol. 10, Su. Elsevier pp. E6-E7., (10.1016/j.clml.2019.09.008)
• Angelopoulos, N. and Wielemaker, J. 2019. Advances in big data bio analytics. Presented at: 35th International Conference on Logic Programming (CLP 2019), Las Cruces, NM, USA, 20-25 September 2019Proceedings 35th International Conference on Logic Programming (Technical Communications), Vol. 306. ETCS pp. 309–322.
• Maura, F.et al. 2019. Genomic landscape and chronological reconstruction of driver events in multiple myeloma. Nature Communications 10, article number: 3835. (10.1038/s41467-019-11680-1)

2018

• Maura, F.et al. 2018. The landscape of structural variant sgnatures in multiple myeloma identifies distinct disease subgroups with implications for pathogenesis. Presented at: 60th American Society of Hematology Annual Meeting, San Diego, CA, USA, 1-4 December 2018, Vol. 132. Vol. Supple. American Society of Hematology, (10.1182/blood-2018-99-112420)
• Maura, F.et al. 2018. The genomic landscape of structural variations and complex events in multiple myeloma. Presented at: XV Congress of the Italian Society of Experimental Hematology, Rimini, Italy, 18-20 October 2018, Vol. 103. Vol. S3. pp. S14.
• Bolli, N.et al. 2018. Analysis of mutations and structural variants to redefine the genomic landscape of multiple myeloma and its clinical implications. Presented at: XV Congress of the Italian Society of Experimental Hematology, Rimini, Italy, 18-20 October 2018, Vol. 103. Vol. S3. Ferrata Storti Foundation pp. S51.
• Grinfeld, J.et al. 2018. Classification and personalized prognosis in myeloproliferative neoplasms. New England Journal of Medicine 379(15), pp. 1416-1430. (10.1056/NEJMoa1716614)
• Mitchell, T. J.et al. 2018. Timing the landmark events in the evolution of clear cell renal cell cancer: TRACERx Renal. Cell 173(3), pp. 611-623.e17. (10.1016/j.cell.2018.02.020)
• Maura, F.et al. 2018. Biological and prognostic impact of APOBEC-induced mutations in the spectrum of plasma cell dyscrasias and multiple myeloma cell lines. Leukemia 32(4), pp. 1043-1047. (10.1038/leu.2017.345)

2017

• Maura, F.et al. 2017. The genomic landscape of multiple myeloma complex structural variations. Presented at: 59th American Society of Hematology Annual Meeting, Atlanta, GA, USA, 9-12 December 2-17, Vol. 130. Vol. Supple. American Society of Hematology, (10.1182/blood.V130.Suppl_1.330.330)
• Maura, F.et al. 2017. Biological and prognostic impact of apobec-induced mutations in the spectrum of plasma cell dyscrasias. Blood 130(Supple), article number: 1771. (10.1182/blood.V130.Suppl_1.1771.1771)
• Angelopoulos, N. and Wielemaker, J. 2017. Accessing biological data as Prolog facts. Presented at: 19th International Symposium on Principles and Practice of Declarative Programming, Namur, Belgium, 9-12 October 2017PPDP '17: Proceedings of the 19th International Symposium on Principles and Practice of Declarative Programming. ACM pp. 29-38., (10.1145/3131851.3131857)
• Grinfeld, J.et al. 2017. Personalized prognostic predictions for patients with myeloproliferative neoplasms through integration of comprehensive genomic and clinical information. Blood 130(Supple), pp. 491. (10.1182/blood.V130.Suppl_1.491.491)
• Angelopoulos, N. and Cussens, J. 2017. Distributional logic programming for Bayesian knowledge representation. International Journal of Approximate Reasoning 80, pp. 52-66. (10.1016/j.ijar.2016.08.004)
• Maura, F.et al. 2017. The apobec mutational activity in multiple myeloma: from diagnosis to cell lines. Presented at: 46th Congress of the Italian Society of Hematology, Rome, Italy, 15-18 October 2017, Vol. 102. Vol. S3. Ferrata Storti Foundation pp. 124.

2016

• Angelopoulos, N., Abdallah, S. and Giamas, G. 2016. Advances in integrative statistics for logic programming. International Journal of Approximate Reasoning 78, pp. 103-115. (10.1016/j.ijar.2016.06.008)
• Favicchio, R.et al. 2016. Choline metabolism is an early predictor of EGFR-mediated survival in NSCLC. Presented at: 107th Annual Meeting of the American Association for Cancer Research, New Orleans, LA, USA, 16-20 April 2016Proceedings of the 107th Annual Meeting of the American Association for Cancer Research, Vol. 76. Vol. 14. Philadelphia, PA, USA: American Association for Cancer Research pp. 4235., (10.1158/1538-7445.AM2016-4235)
• Angelopoulos, N.et al. 2016. Proteome-wide dataset supporting functional study of tyrosine kinases in breast cancer. Data in Brief 7, pp. 740-746. (10.1016/j.dib.2016.03.024)
• Nunes, J.et al. 2016. ATG9A loss confers resistance to trastuzumab via c-Cbl mediated Her2 degradation. Oncotarget 7(19), pp. 27599-27612. (10.18632/oncotarget.8504)

2015

• Stebbing, J.et al. 2015. Characterization of the Tyrosine Kinase-Regulated Proteome in Breast Cancer by Combined use of RNA interference (RNAi) and Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC) Quantitative Proteomics. Molecular and Cellular Proteomics 151, pp. 555–568. (10.1074/mcp.M115.048090)
• Xu, Y.et al. 2015. LMTK3 represses tumor suppressor-like genes through chromatin remodeling in breast cancer. Cell Reports 12(5), pp. 837-849. (10.1016/j.celrep.2015.06.073)
• Zhang, H.et al. 2015. Proteomic profile of KSR1-regulated signalling in response to genotoxic agents in breast cancer. Breast Cancer Research and Treatment 151(3), pp. 555-568. (10.1007/s10549-015-3443-y)
• Angelopoulos, N. and Giamas, G. 2015. A logical approach to working with biological databases. Presented at: 31st International Conference on Logic Programming (ICLP 2015), Cork, Ireland, 31 August - 4 September 2015Proceedings of the Technical Communications of the 31st International Conference on Logic Programming (ICLP 2015), Vol. 1433. CEUR
• MacIntyre, D. A.et al. 2015. The vaginal microbiome during pregnancy and the postpartum period in a European population. Scientific Reports 5, article number: 8988. (10.1038/srep08988)
• Spanjaard, E.et al. 2015. Quantitative imaging of focal adhesion dynamics and their regulation by HGF and Rap1 signaling. Experimental Cell Research 330(2), pp. 382-397. (10.1016/j.yexcr.2014.10.012)

2010

• Husi, H.et al. 2010. Selective chemical intervention in the proteome of Caenorhabditis elegans. Journal of Proteome Research 9(11), pp. 6060–6070. (10.1021/pr100427c)

2009

• Angelopoulos, N., Hadjiprocopis, A. and Walkinshaw, M. D. 2009. Bayesian model averaging for ligand discovery. Journal of Chemical Information and Modeling 49(6), pp. 1547-1557. (10.1021/ci900046u)
• Angelopoulos, N. and Cussens, J. 2009. Bayesian learning of Bayesian networks with informative priors. Annals of Mathematics and Artificial Intelligence 54, pp. 53-98. (10.1007/s10472-009-9133-x)

2001

• Angelopoulos, N. and Cussens, J. 2001. Markov chain Monte Carlo using tree-based priors on model structure.. Presented at: 17th The Conference on Uncertainty in Artificial Intelligence (UAI 2001), Seattle, WA, USA, 2-5 August 2001 Presented at Breese, J. and Koller, D. eds.UAI'01: Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence. San Francisco, USA: Morgan Kaufmann Publishers Inc., (10.5555/2074022.2074025)