Linear Control Theory for Gene Network Modeling

Linear Control Theory for Gene Network Modeling

Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and fee...

Control theory for linear systems

Statecharts for Gene Network Modeling

State diagrams (stategraphs) are suitable for describing the behavior of dynamic systems. However, when they are used to model large and complex systems, determining the states and transitions among them can be overwhelming, due to their flat, unstratified structure. In this article, we present the use of statecharts as a novel way of modeling complex gene networks. Statecharts extend conventio...

Modeling gene regulatory networks: Classical models, optimal perturbation for identification of network

Deep understanding of molecular biology has allowed emergence of new technologies like DNA decryption.  On the other hand, advancements of molecular biology have made manipulation of genetic systems simpler than ever; this promises extraordinary progress in biological, medical and biotechnological applications.  This is not an unrealistic goal since genes which are regulated by gene regulatory ...

Network Theory Tools for RNA Modeling.

An introduction into the usage of graph or network theory tools for the study of RNA molecules is presented. By using vertices and edges to define RNA secondary structures as tree and dual graphs, we can enumerate, predict, and design RNA topologies. Graph connectivity and associated Laplacian eigenvalues relate to biological properties of RNA and help understand RNA motifs as well as build, by...