Overview

The central theme of the Center is the multiscale analysis of cellular networks. Cellular processes are determined by the concerted activity of thousands of genes, their products, and a variety of other molecules. This activity is coordinated by a complex network of biochemical interactions which control common intra- and inter-cellular functions over a wide range of scales. Understanding this organization is crucial for the elucidation of biological function and for framing health related applications in a quantitative, molecular context.

MAGNet investigators apply a combination of knowledge-based and physics-based methods to study the organizational principles that underlie the operation of cellular networks. A basic tenet of the Center's research program is the notion that by bridging together and integrating molecular-interactions across multiple levels of granularity (from the atomic to the macroscopic) and by using multiple data modalities (from structural coordinates to genetic and epigenetic variability) accelerated progress can be achieved, both within and across research domains.

The theme of the Center is manifested in a number of Driving Biological projects (DBPs) that target broad areas of basic research, including:

1. tackling the issue of biomolecular interaction directly, at the structural and physiochemical level,
2. constructing context-specific maps of cellular interactions, and
3. using such maps to dissect complex diseases.

The biological questions posed by the DBPs generate the requirements that drive the computational research carried out by the Center's investigators. This work involves both the development of novel analytical frameworks (basic computational research) as well as the development of tools and models that leverage these frameworks (applied computational research):

• Basic Computational Research addresses general computational and algorithmic challenges raised by the DBPs. Research activities include the development of
  
  1. machine Learning (ML) algorithms for evidence integration, classification, and inference,
  2. natural language processing algorithms, and
  3. software engineering methodologies and frameworks for the assembly of the center repository based software platform.
• Applied Computational Research focuses on the development of novel algorithms and tools to support specific biomedical applications. The approaches used are both knowledge-based and physics-based and incorporate the methods yielded by efforts in basic research. Algorithms are combined with existing and new databases to build a modular and extensible bioinformatics platform (geWorkbench) and an associated software toolkit for the analysis of biomolecular interactions.

To support biomedical computation research the MAGNet Center leverages a world-class information technology infrastructure. Additionally, MAGNet's Training Core ensures that the methods developed by the Center are integrated into the educational offerings of Columbia University's Medical School.