Using information theory to analyze and predict splicing mutations in rare and common diseases: performance and best practices. <\/strong>N.G.\u00a0<\/strong>Caminsky, E. Mucaki\u00a0and P.K. Rogan<\/p>\n Reversing differences in chromatin accessibility that distinguish homologous mitotic metaphase chromosomes<\/strong>. W.A. Khan, P.K. Rogan, J.H.M. Knoll<\/p>\n Automated Dicentric Chromosome Identification by Machine Learning-based Image Processing.<\/strong> P.K.\u00a0Rogan, Y. Li, A. Subasinghe, J. Samarabandu, R. Wilkins and J.H. Knoll<\/p>\n Towards the minimal breast cancer genome and its relevance to chemotherapy.<\/strong>\u00a0S.N. Dorman, J.H. Knoll, K. Baranova, C. Viner, P.K. Rogan<\/p>\n The FANCM c.5791C>T nonsense mutation (rs144567652) induces exon skipping and is a risk factor for familial breast cancer.<\/strong> Paolo Peterlongo , \u00a0Francesca Damiola, Eliseos Mucaki, \u00a0Valentina Dall\u2019Olio ,Sara Pizzamiglio \u00a0, Irene Catucci , \u00a0Anders Kvist , Paolo Verderio, Mara Colombo , Loris Bernard , \u00a0Hans Ehrencrona, Laura Caleca, Valeria Pensotti , Sylvie Mazoyer, Peter K. Rogan ,Paolo Radice<\/p>\n <\/p>\n