As more is uncovered about the dynamic inner workings of genes and proteins, researchers now face the happy—if sometimes vexing—problem of working with too much data. But in the onslaught, crucial connections can be missed and findings repeated.

In the past decade, many a ponderous computer program and dense database has assisted in sorting this surplus of scientific knowledge into serviceable research tools. But finding a friendlier interface to illustrate and investigate all of the molecular players involved in the time-dependent process of gene expression has been difficult. 

A new piece of software might help to solve the problem. Announced last month online in the journal Bioinformatics, this program uses a clustering algorithm to turn genetic regulation processes into mini, data-rich movies. These animations allow researchers to play, pause and dive into molecular-level changes in genes and proteins—and see how they work together. The program, called Grid Analysis of Time Series Expression (GATE), pairs the movies with  databases built from reams of previous research and also allows researchers to input their own data for analysis. The result is "animated movies which illustrate systems level molecular expression dynamics," wrote the authors of the paper describing the program.

"GATE can help biologists to dynamically interact with high-dimensional complex time-series data," Avi Ma'ayan, an assistant professor in Mount Sinai School of Medicine's Department of Pharmacology and Systems Therapeutics in New York and one of the collaborators on the project, wrote in an email. "It is the only program that combines movies of clustered temporal expression with background knowledge datasets such as protein-protein interactions and annotated gene sets." The program's creators hope that this combination—along with the capability to integrate additional data sets—will allow for a new, more nuanced measurement of detailed genetic processes. And the colorful geometric animations should make it easier to navigate and present.

The software came out of collaboration amongst biologists, mathematicians, software developers and others at Mount Sinai—all of whom were looking for a better way to visualize and analyze dense genetic information.

Some of the program's developers have already made use of its illustrative—and analytic—capabilities. In a paper co-authored by Ma'ayan, researchers used the program to document cell fate changes in embryonic stem cells in a paper published November 19 in Nature (Scientific American is part of Nature Publishing Group). "Such data is challenging to analyze," Ma'ayan wrote about measuring mRNA, whole nuclear proteomics and other factors. "The paper is the first that measures so many things on a time course in mammalian cells." As a final flourish, the authors claimed another first by embedding versions of the interactive movies within their published supporting materials.

Image of GATE courtesy of the Ma'ayan Laboratory at Mount Sinai