Filippo Menolascina - Bioinformatics Group IRCCS of Bari

Eng. Filippo Menolascina covers the role of Main Researcher at the Bioinformatics Research Group of the Italian branch of National Cancer Institute in Bari since its settlement in 2006.

Bio

Filippo Menolascina was born in Bari (Italy) in 1984 and received his Laurea degree (B. Eng) in Computer Engineering from the Polytechnic of Bari in 2006. He is a member of the Italian branch of IEEE and IAENG international associations. Eng. Menolascina is even a member of the Bioinformatics Interdisciplinary Group of the Polytechnic of Bari and National Cancer Institute of Bari. His main research topics are focused on the development of Intelligent Systems in the biomedical and bioinformatic fields with a particular focus on bioinspired data mining algorithms. He has published several papers and abstracts in refereed journals, international conferences proceedings and chaired a session in Bioinformatics at the CIMCA conference in 2005.

Research Interests

The research interests of Eng. Menolascina are mainly focused on the design of bioinspired techniques in the computational intelligence field with applications to computational biology and bioinformatics. In particular he has experienced the employment of advanced data modelling and optimization (e.g. Artificial Neural Networks and Genetic Algorithms / Programming) techniques in hybrid expert systems. His current research activity is centered on the exploitation of Artificial Immune System paradigms as both data mining systems (IFRAIS) and combinatorial optimization techniques (Clonalg) by means of Clonal Selection and Negative Selection principles. Together with the previous ones, Gene Expression Programming inspired techniques are being used in order to model complex biological interactions between genetic actors in oncology from microarray and HT experiments.

Other area of research covered by Eng Menolascina's activity lay in intelligent medical image segmentation (CAT and X-ray), automated extraction of ROIs and computer vision in biometrics.

Programme Committee Memberships

ICIC 2007 - International Conference on Computational Intelligence

WIVACE 2007 - Workshop Italiano di Vita Artificial e Computazione Evolutiva

Reviewer

ICIC 2006 - International Conference on Computational Intelligence

IAENG Special Issue on Bioinformatics - December 2006

Genetic Programming and Evolvable Machines, Special Issue on applications in medicine

ACST 2007 - Advances in Computer Science and Technology

KES/IMBS 2007 - Knowledge Extraction Systems / Invited Session on IMmunity Based Systems

Contacts

Address: Clinical and Experimental Oncology Laboratory, IRCCS "Giovanni Paolo II", Bari

Via F. Hahnemann, 10

70126, Bari - Italy

Office: +39 080 555 55 31

Fax: +39 080 555 27 31

E-mail: bioinformatics.losc at oncologico.bari.it (with at = @)

Publications

V. Bevilacqua, G. Mastronardi and F. Menolascina, Hybrid data analysis methods and Artificial Neural Network design in breast cancer diagnosis: IDEST experience, CIMCA 2005.

V. Bevilacqua, G. Mastronardi and F. Menolascina, Microarray Data Analysis Using Hybrid Intelligent System: Biological Validity Assessment and Comparative Studies, ICIC 2006

V. Bevilacqua, G. Mastronardi, F. Menolascina, P. Pannarale and A. Pedone, A Novel Multi-Objective Genetic Algorithm Approach to Artificial Neural Network Topology Optimisation: The Breast Cancer Classification Problem, IJCNN 2006

V. Bevilacqua, G.Mastronardi, Filippo Menolascina, A. Paradiso and S. Tommasi, Genetic Algorithms and Artificial Neural Networks in Microarray Data Analysis: a Distributed Approach, Engineering Letters, Special Issue on Bioinformatics (December 2006)

S. Tommasi, F. Menolascina, V. Fedele, D. Albertson, C.C. Benz, V. Bevilacqua and A. Paradiso, New Statistic tools for high density array analysis in breast cancer. SIC 2006

S. Tommasi, F. Menolascina, V. Fedele, D. Albertson, C.C. Benz, M. Bruno, R. Pinto,M. lo mele, A. Mangia, V. Bevilacqua, A. Paradiso, aCGH Profile in familial breast cancer, SIC 2006

Vitoantonio Bevilacqua, Giuseppe Mastronardi, Filippo Menolascina,Angelo Paradiso, Stefania Tommasi, Hybrid Intelligent Data Mining Techniques and Array CGH in Breast Cancer Profiling, Proceedings of 2006 Workshop on Intelligent Computing & Bioinformatics of CAS, ISBN 7-312-02014-5/Q.43, November 12-14, 2006 Hefei, China, pp. 93-99

V. Bevilacqua, G. Mastronardi, F. Menolascina “Intelligent Information Structure Investigation in Biomedical Databases: The Breast Cancer Diagnosis Problem”, to appear in Proceedings of International Conference on Intelligent Systems and Control (ISC 2005), October 31 – November 2, 2005, Cambridge, USA.

Menolascina F. Tommasi S., Paradiso A., Cortellino M., Bevilacqua V., Mastronardi G. Novel Data Mining Techniques in a CGH based Breast Cancer Subtypes Profiling: the biological perspective to appear on Proceedings of 2007 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, April 1-5, 2007 – Honolulu – US

Chiarappa P., Rossi E., Mangia A., Tommasi S., Menolascina F., Pilato B., Ottini L., Zoli W., Zuffardi O., Paradiso A., Genomic alterations in male breast cancers by aCGH, Abs in IX Congresso Nazionale SIGU, Venezia 2006.

Tommasi S., Menolascina F., Pilato B., Bruno M., Pinto R., Campana M., Chiarappa P., Bevilacqua V., Paradiso A., New bioinformatics tools for genomic studies of familial breast cancer. Abs in AACR Annual Meeting, April 14-18, 2007

Menolascina F. et al, Stereo-Matching Techniques Optimisation Using Evolutionary Algorithms, in Proceedings of ICIC 2006, Lecture Notes in Computer Science, Springer-Verlag

V. Bevilacqua, F. Menolascina et al: Hybrid Systems and Artificial Immune Systems: Performances and Applications to Biomedical Reasearch, ISNN 2007

Menolascina, Chiarappa et al: Data Mining techniques in aCGH based breast cancer subtype profiling: an immune perspective with comparative study, Systems Biology, in press

Menolascina, Alves et al: Induction of Fuzzy Rules with Artificial Immune Systems in aCGH based ER Status Breast Cancer Characterization, GECCO 2007, submitted

Menolascina, Alves et al: A Comprehensive Bioinspired Data Mining Approach to Estrogen Receptor Characterization in Breast Cancer, ISMB 2007, submitted