Estimation of life expectancy of patients diagnosed with the most common cancers in the Valparaiso Region, Chile.

BACKGROUND: The 1000s of people who die from cancer each year have become one of the leading causes of death among the Chilean population, placing it as the second cause of death in the region of Valparaiso between 1997 and 2003. Statistics have provided different measures regarding the life expectancy of cancer patients which have resulted in being useful to establish courses of action for prevention and treatment plans to follow. METHODS: Data was extracted from the cancer module of the Epidemiology Assistance System (SADEPI for its initials in Spanish) which stores information about cancer cases in the provinces of Valparaiso and Petorca. The survival period is defined as the difference in days between the date of occurrence and the date of death of the patient by separating the data into quartiles. RESULTS: The more frequent cancers in the region of Valparaiso behave similarly to global behaviours of the disease. The majority of affected patients are around 65 years of age which progressively lowers its occurrence in younger adults under the age of 45. CONCLUSIONS: Further efforts are required for early detection and timely access to treatment for cancer patients. Statistics are an important support in achieving this.

On the number of different dynamics in Boolean networks with deterministic update schedules.

Deterministic Boolean networks are a type of discrete dynamical systems widely used in the modeling of genetic networks. The dynamics of such systems is characterized by the local activation functions and the update schedule, i.e., the order in which the nodes are updated. In this paper, we address the problem of knowing the different dynamics of a Boolean network when the update schedule is changed. We begin by proving that the problem of the existence of a pair of update schedules with different dynamics is NP-complete. However, we show that certain structural properties of the interaction diagraph are sufficient for guaranteeing distinct dynamics of a network. In [1] the authors define equivalence classes which have the property that all the update schedules of a given class yield the same dynamics. In order to determine the dynamics associated to a network, we develop an algorithm to efficiently enumerate the above equivalence classes by selecting a representative update schedule for each class with a minimum number of blocks. Finally, we run this algorithm on the well known Arabidopsis thaliana network to determine the full spectrum of its different dynamics.

Mathematical methods for inferring regulatory networks interactions: application to genetic regulation.

This paper deals with the problem of reconstruction of the intergenic interaction graph from the raw data of genetic co-expression coming with new technologies of bio-arrays (DMA-arrays, protein-arrays, etc.). These new imaging devices in general only give information about the asymptotical part (fixed configurations of co-expression or limit cycles of such configurations) of the dynamical evolution of the regulatory networks (genetic and/or proteic) underlying the functioning of living systems. Extracting the casual structure and interaction coefficients of a gene interaction network from the observed configurations is a complex problem. But if all the fixed configurations are supposedly observed and if they are factorizable into two or more subsets of values, then the interaction graph possesses as many connected components as the number of factors and the solution is obtained in polynomial time. This new result allows us for example to partly solve the topology of the genetic regulatory network ruling the flowering in Arabidopsis thaliana .

Mathematical modeling in genetic networks: relationships between the genetic expression and both chromosomic breakage and positive circuits.

The human genome with its 23 pairs of chromosomes, is the result of evolution. This evolution has been ruled by the mutation process and also by the physiological and pathological reorganization of the genomic material inside or between the chromosomes, which are conditioning the genomic variability. This reorganization is starting at singular points on the short or long chromosomic arms, called crossing-over, or translocations, insertions, break points. In this paper, we will show that these points, also called weak points or hot spots of the genome are correlated, independently of their origin. In addition, we will give some properties of the genetic interaction matrices in terms of attractors of the genetic expression dynamics.