“We started noticing, about five years ago, that a lot of people in pharmaceutical companies were buying Matlab and using it for dynamic simulations of pathways,” says Rick Paxson, manager, systems biology group. “We attempted to educate them on SimuLink®, which wasn’t really geared toward biologists. That’s why we built SimBiology.”
The software addresses a major hurdle —a lack of graphical language to represent pathways. It enables researchers to simulate the modeled reactions and then analyze the resulting data or perform custom analysis with Matlab.
“When you go on the net and search for how some companies might be using pathways to represent biological systems, they use different symbols. We’ve developed a minimal language that does that job, and we will continue to improve it in future versions,” adds Paxson.
SimBiology further helps focus on potential drug targets within pathways with its automation of sensitivity analysis. Its parameter estimation functionality also lets users generate estimates for unknown parameters within an existing model.
In addition, SimBiology allows loading of data file formats from different platforms (e.g., Affymetrix; www.affymetrix.com) directly into Matlab and allows the user to annotate models with notes from literature or other sources.
Ariadne Genomics (www.ariadnegenomics.com) licensed its Pathway Studio® software to Murex Pharmaceuticals to develop computer-based models for the identification and validation of cancer targets.
“When we were working on a gene expression project, we realized that the next step to microarray analysis is via the analysis of pathways,” states Ilya Mazo, Ph.D., company president. “People need to understand the biology behind why certain genes are differentially regulated between normal and cancer states. That’s where Pathway Studio comes in.”
This software helps interpret experimental results in terms of pathways, gene regulation networks, and protein-interaction maps and automatically extracts information from scientific literature. It also reconstructs pathways from the user’s microarray and other data.
After inputting a set of genes and/or proteins or a microarray experiment to initiate database mining, the software retrieves the most relevant networks that are differentially altered in a disease or provides information about common regulatory mechanisms of the gene set. The found networks are displayed and can be validated by referring back to the original article where the facts originated. New networks can be further analyzed by comparing them to known pathways.
The MedScan™ technology, which extracts information from PubMed and 43 full-text journals, is a unique feature to this software, according to Dr. Mazo. This is done using the company’s NLP (Natural Language Processing) tool. “We’re not trying to tell people which data is good or bad. We give them a tool so they can find the data that they need,” states Dr. Mazo.