MIDGET:Detecting differential gene expression on microarray data.

Backgound and Objective: Detecting differentially expressed genes is an important step in genome wide analysis and expression profiling. There are a wide array of algorithms used in today's research based on statistical approaches. Even though the current algorithms work, they sometimes miss-predict.

Stress Detection Using Wearable Physiological and Sociometric Sensors.

Stress remains a significant social problem for individuals in modern societies. This paper presents a machine learning approach for the automatic detection of stress of people in a social situation by combining two sensor systems that capture physiological and social responses. We compare the performance using different classifiers including support vector machine, AdaBoost, and [Formula: see text]-nearest neighbor.

Morphometrical differences between resectable and non-resectable pancreatic cancer: a fractal analysis.

Background/aims: Pancreatic cancer is a highly aggressive cancer with a rising incidence and poor prognosis despite active surgical treatment. Candidates for surgical resection should be carefully selected. In order to avoid unnecessary laparotomy it is useful to identify reliable factors that may predict resectability.

Network based models for biological applications.

This paper analyses the adequacy of different types of networks in biological process modeling. The assumptions are sustained by two case studies. The first one is a lattice-based computer model to simulate the growth of nonvascular tumors with nutrient consumption constraints.

Modelling celullar communication with scale-free networks.

The paper proposes a model that brings to light the characteristics of several complex systems having similar scale-free network architecture. The properties of this kind of network are compared with those of other methods which are specific for studying complex systems: nonlinear dynamics and statistical methods. We place particular emphasis on scale-free network theory and its importance in enhancing the framework for the quantitative study of complex biological systems.