• Electronic Design Automation - EDA/CAD:
  • Systems-on-chip, circuit and device optimization, circuit sizing, and design for yield - Academic Network - Cadence Design Systems Inc.;
  • Global Optimisation Trajectory Problems and Solutions by European Space Agency (ESA) - Global Optimisation Trajectory Problems (GTOP) database;
  • numerical and combinatorial optimization, and multi-objective optimization; the design and analysis of algorithms and systems for optimization and machine learning.
• Biological Design Automation:
  • biological design automation, biological circuit design, sensitivity analysis, robustness analysis;
  • inferring biological pathways, protein structure prediction, protein folding, and protein robustness;
  • design of biological circuits, design of Artificial Immune Systems;

Biological Circuit Design This research project focuses on the application of algorithms, mathematical methods and engineering principles to the design, analysis, optimization, implementation, and programming of biological systems, and on the discovery and application of new engineering and computational principles inspired by the properties of biological systems. design of biological circuits; inferring pathway and parameter extraction; design of Artificial Immune Systems

Structural Bioinformatics protein structure prediction; protein folding; protein robustness. A recent review paper published by the Journal of the Royal Society Interface, G. Helles,(2008; 5(21): 387--396) ranks our I-PAES algorithm among the best state-of-art folding algorithm; in fact, I-PAES (i-paes.zip) is the 3rd-4th best folding algorithm (see tables 1 and 2 of the paper). V. Cutello, G. Narzisi, G. Nicosia,A Multi-Objective Evolutionary Approach to the Protein Structure Prediction Problem, J. of the Royal Society Interface, 3(6):139-151, 2006. Description ...

Learning in the Natural and Artificial Immune Systems learning during primary and secondary response of the immune system; pattern recognition by clonal election principle; clonal selection algorithms and immunological algorithms. Description ...

Electronic Design Automation - EDA/CAD circuit and device design; circuit sizing; design for yield.

Numerical and Combinatorial Optimization numerical optimization; combinatorial optimization; multi-objective optimization.

• Dr. G. Narzisi, Ph.D. in Computer Science, completed 2008. Post-Doc at Bioinformatics Group of New York University, NY, USA. Giuseppe Narzisi won IBM Ph.D. Fellowship Award. Currently Giuseppe is a Computational Science Analyst at the Simons Center for Quantitative Biology (SCQB) of Cold Spring Harbor Laboratory (CSHL), New York, USA.
• Dr. G. Stracquadanio, Ph.D. in Computer Science. Now Post-Doc at Johns Hopkins University, MD, USA.
• Dr. E. Sciacca, Ph.D. in Mathematics for Technology. Now Post-Doc at University of Torino, Italy.
• Dr. Renato Umeton, Ph.D. in Computer Science. From January to April 2009: Visiting Ph.D. Student at Computational Systems Biology - COSBI, Microsoft Research Center - University of Trento, Italy. Visiting Ph.D. student at MIT. Now Post-Doc at the University of Rome "La Sapienza", Italy.
• Jole Costanza, Ph.D. student in Computer Science - University of Catania, Italy, 2010 - 2013.
• Claudio Angione, Ph.D Student in Computer Science - University of Cambridge, UK, 2011-2014.

• C. J. Love, graduate Student at the Chemical Engineering Dept. - Center for Biomedical Engineering - MIT, Catania June-July 2009.
• Piero Conca, Computer laboratory, University of York, UK.
• N. Agila, undergraduate student at the Computer Science Artificial Intelligence Lab. CSAIL - MIT, Catania June-July 2008.
• Rosario Rascuna', Computer laboratory, University of Essex, UK.
• Peter Oliveto, graduate student, University of Catania, Laurea in 2006.

• Annalisa Occhipinti, University of Cambridge - Computer Lab., UK.
• Manuel Aprile, University of Oxford - Computer Lab, UK.
• Antonio Cauchi, Stockholm University - Department of Mathematics, Sweden.
• I. Martino, Graduate Student, Scuola Superiore di Catania/Institute for Advanced Studies. Ivan Martino won the Anile Prize 2009. Now PhD student at the Department of Mathematics at Stockholm University, Sweden.
• C. Angione, Graduate Student, Scuola Superiore di Catania/Institute for Advanced Studies, Now PhD student at the Computer Lab, University of Cambridge, UK. Claudio Angione won the Anile Prize 2011.
• G. Platania, Visiting M.Sc. Student at Electrical Engineering and Computer Sciences Department, University of California Berkeley, USA, Fall 2011.

• I-PAES Algorithm Code (I-PAES)
  I-PAES is a modified version of the multi-objective evolutionary algorithm PAES (Pareto Archived Evolution Strategy), proposed by Knowles and Corne in 1999, with a different solution representation (polypeptide chain) and immune inspired operators (cloning and hypermutation) for the Protein Structure Prediction problem (PSP).
  
  References
  • V. Cutello, G. Narzisi, G. Nicosia, A Multi-Objective Evolutionary Approach to the Protein Structure Prediction Problem, J. of the Royal Society Interface, 3(6):139-151, 2006.
  • V. Cutello, G. Narzisi, G. Nicosia,
    A Class of Pareto Archived Evolution Strategy Algorithms Using Immune Inspired Operators for Ab-Initio Protein Structure Prediction. EvoWorkshops 2005 - EvoBio 2005, Lausanne, Switzerland, 30 March - 1 April, 2005, Proceeding by LNCS, vol. 3449, pp. 54-63 Springer.
  
  Notes
  I-PAES code uses some external routines from the TINKER Molecular Modeling Package:
  • analyze
  • protein
  • xyzpdb
  and the force field parameter set of CHARMM (version 27) energy function (charmm27.prm).
  You can download these files directly from the TINKER web-site that you find in the following Resources section. ("Readme" file in the I-PAES package contains informations about the installation of these external files in the software and the compilation of the overall code).
  
  Resources
  • i-paes.zip - C language code of I-PAES incorporating scripts and input files for 1ZDD protein (Linux version).
  • TINKER Molecular Modeling Package.

Complexity

Giuseppe Nicosia, Optimization, Combinatorial Optimization, Numerical Optimization, Non Linear Optimization, Large Scale Optimization, Evolutionary Algorithms, Genetic Algorithms, Immune Algorithms, Artificial Immune Systems, Graph Coloring, String Folding, NP-complete problems, Circuit Optimization, Circuit Design, Design For Yield, Device Optimization, Bioinformatics, Structural Bioinformatics, Protein Folding, Protein Structure Prediction, HP model.