NeMo: A network modeling server for biological pathway analysis.
High-throughput genomic and proteomic technologies have recently enabled unprecedented
views of gene and protein expression in cellular systems. These methods provide a staggering
amount of data, even in modest experiments, and effective interpretation of the data is highly
dependent on advanced computational techniques to analyze, manage, and visualize the results.
The integration of computational biology and “omics” technologies has spawned the systems
biology approach towards characterizing cellular events on a broad scale, including elucidation of
complex networks of genes and proteins, and their regulatory mechanisms. These approaches
require numerous, highly specialized computational tools and the associated skills, which are
generally out of reach to most investigators. An important objective towards providing systems
biology capabilities to the general research community is the development and integration of
cohesive, web-accessible tools and databases that can be utilized by non-specialists. The proposed
research will develop a network modeling system comprised of a high-throughput genomic and
proteomic database and associated computational tools to enable predictions of cellular networks.
Initially, the database will be populated with data and models for one of the most important
signaling pathways in biomedical research: the PI3K/Akt/mTOR pathway. The computational
framework developed in this research will be extensible to facilitate inclusion of other signaling
pathways and data types.
Our long-term goal is to identify the topography of regulatory networks critical to cellular
processes and disease progression through the development of computational methods and their
application to high throughput genomic and proteomic data. The objective of this application is to
develop a database and tools that will provide models of transcriptional regulation controlled
through the PI3K/Akt/mTOR cascade using a systems biology approach. Subsequent work will
focus on extending this approach to other signaling cascades along with the integration of other
high-throughput data types such as ChIP on chip and microRNA array data.