Nome del laboratorio ed ente di afferenza:
Scientific Computing and data Analysis Laboratory, Università del Sannio
Responsabile/referente: Prof. Michele Ceccarelli
Descrizione sintetica delle attività svolte:
Analisi sviluppo ed applicazione di metodologie algoritmiche basate su machine learning e soft computing per l’analisi di dati, segnali e forme in campo biologico.
Risorse hw/sw disponibili:
Cluster di workstation, diversi software di PSE (Problem Solving Environments) sia di tipo commerciale che open source
Pubblicazioni nel campo bioinformatico - biocomputazionale (max. 5):
1. M. Ceccarelli and A. Maratea, “Virtual genetic coding and time series analysis for alternative splicing prediction in C.elegans,” Artificial Intelligence in Medicine, 2008. to appear.
2. M. Ceccarelli and A. Maratea, “Improving fuzzy clustering of biological data by metric learning with side information,” International Journal of Approximate Reasoning, vol. 47, pp. 45–57, January 2008.
3. G. Antoniol and M. Ceccarelli, “Microarray image gridding with stochastic search based approaches,” Image and Vision Computing, vol. 25, no. 2, pp. 155–163, 2007.
4. M. Ceccarelli and G. Antoniol, “A deformable grid-matching approach for microarray images,” IEEE Transactions on Image Processing, vol. 15, no. 10, pp. 3178–3188, 2006.
5. M. Ceccarelli and A. Maratea, “Assessing clustering reliability and features informativeness by random permutations,” Lecture Notes in Computer Science, vol. 4694, pp. 878– 885, Springer, 2007.