Emilio Mastriani

Genetic algorithm against cancer

We present an evolutionary approach to the search for effective vaccination schedules using mathematical computerized model as a fitness evaluator. Our study is based on our previous model that simulates the Cancer – Immune System competition activated by a tumor vaccine. The model reproduces pre-clinical results obtained for an immunoprevention cancer vaccine (Triplex) for mammary carcinoma on HER-2/neu mice. A complete prevention of mammary carcinoma was obtained in vivo using a Chronic vaccination schedule. Our genetic algorithm found complete immunoprevention with a much lighter vaccination schedule. The number of injections required is roughly one third of those used in Chronic schedule.

HAMFAST: Fast Hamming Distance Computation

Similarity is a vague concept which can be treated in a quantitative manner only using appropriate mathematical representation of the objects to compare and a metric on the space representation. In biology the mathematical representation of structure relies on strings taken from an alphabet of m symbols. Very often binary strings, m = 2, are used. The size of the binary string depends on the complexity of the structure to represent, so the string can be quite long. The Hamming distance is the most used metric with binary strings. The computational effort required to compute the Hamming distance linearly depends on the size of the string. However even a linear effort case may be computational heavy if many computations are required. One of the fastest computational approach to evaluate Hamming distances relies on look-up tables. The computational performance, however, rapidly deteriorates with the size of binary string length, due to cache misses. We present a computational strategy and implementation which can handle huge number of Hamming distance evaluation between binary strings of arbitrary length keeping computational performance competitive.

SIMULATED ANNEALING AND OPTIMAL PROTOCOLS

Many human tumors cannot easily be avoided. In most cases a prophylactic vaccination prevents the tumor growth. In particular the Triplex vaccine prevented mammary carcinoma formation using a Chron...

Model deconstruction of an immunoprevention vaccine

We present a further step in developing an in silico model that simulates the immune system responses to tumor cells in vaccinated mice. Our study is based on our previous model that simulates the cancer – immune System competition activated by a tumor vaccine. In what follows, we show first results on effects of deconstructing the components of Triplex vaccine that are in very good agreement with in vivo results.

Towards a Personalized Schedule with Triplex Vaccine

The immune system is a large and complex system still incompletely understood. The synergy of biological knowledge included in data bases, mathematical and computational models and bioinformatics tools can help in gain a deeper understanding. In this paper, we try to understand how one can characterize a mouse in order to find the better vaccination protocol against mammary carcinoma for that individual. This study will be expanded in the framework of ImmunoGrid EC project.