My research interests lie in the development of new technologies for application-oriented projects in biomedical, biotechnology, and computer sciences. Topics of interest are but not limited to computational biology, artificial intelligence, optimization algorithms, consensus-based methods, graph theory, image processing, software development, and human-computer interaction.
Reverse engineering biological organisms
The goal of the reverse engineering algorithm is to generate a computer model that accurately describes a specific organism. Though the generation of whole models belongs presently in science fiction, such models hold the promise of powerful predictive capabilities. As an example, I believe it will be possible one day to simulate the effect of drugs using a customized computer model of a patient before effectively applying a treatment.
Significant efforts have been put into reverse engineering gene regulatory networks, the normal functioning of which plays a central role in the development and health of any organism. Numerous methods have been developed for reverse engineering gene regulatory networks from expression data. However, 1) both their absolute and comparative performance remain poorly understood and 2) there are usually not enough in vivo data available to generate accurate computer models.
Yet another important contribution of my thesis is that I have implemented the methods developed as open-source, extensible, and user-friendly computational tools. Please click on one of the following images for more information about the applications.