Computation for Design, Optimization & Systems Biology
- Synthetic and Systems Biology:
- biological design automation, BioCAD, biological circuit design, sensitivity analysis, robustness analysis;
- inferring biological pathways, protein structure prediction, protein folding, and protein robustness;
- artificial leaf; flux balance analysis; metabolic engineering; apoptosis; bioengineering;
- design of biological circuits, design of Artificial Immune Systems;
- Design Automation:
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.
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.
- circuit and device design;
- circuit sizing;
- design for yield.
Giuseppe Nicosia, Associate Professor of Computer Engineering.
Post-Doc and PhD Students
- 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.
Undergraduate and Graduate Students
- 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
(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).
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,
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.
I-PAES code uses some external routines from the TINKER Molecular Modeling Package:
and the force field parameter set of CHARMM (version 27) energy
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).
i-paes.zip - C language code of I-PAES
incorporating scripts and input files for 1ZDD protein (Linux version).
TINKER Molecular Modeling Package.
Copyright 2002-2012, 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.