Employing small-shuffle surrogate technique to understand the deterministic levels of cancer data

• Grant number: 14/20430-2
• Support Opportunities: Scholarships abroad - Research Internship - Scientific Initiation
• Effective date (Start): December 07, 2014
• Effective date (End): March 06, 2015
• Field of knowledge: Physical Sciences and Mathematics - Computer Science
• Principal Investigator: Rodrigo Fernandes de Mello
• Grantee: Anderson Caio Santos Silva
• Supervisor: Michael Small
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Research place: University of Western Australia (UWA), Australia
• Associated to the scholarship: 14/03352-8 - Application of time series analysis to model and understand Cancer indices, BP.IC

Abstract

Several systems or other phenomena produce outputs, i.e., results, which can be collected over time. Phenomena related to medicine are of particular interest due to they affect people's quality of life. Among such phenomena, there is interest in understanding under which conditions the cancer disease occurs and what are its relationships to other factors or variables such as habits, geographic regions, etc. In this context, this work is an extension of the undergraduate research project 1 which analyzes time series in terms of determinism and stochasticity, i.e., if they are better represented by Dynamical Systems or Statistic branch and also correlates indices of cancer occurrences in order to understand such phenomenon. In that sense, this work employs an additional tool, proposed by Prof. Michael Small, University of Western Australia, to measure determinism levels of time series. Prof. Small accepted to host the student who proposes this work and provide him more information and help to apply his method on cancer data. This is a very important opportunity to strengthen the scientific partnership between both groups. As result, we expect to better understand the deterministic features of cancer occurrences and report them through papers. (AU)