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Active Motif Sees Double-Digit Growth in Time Logic Group, New Deals for AKS2

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Active Motif this week announced that the Translational Genomics Research Institute had licensed its AlmaKnowledgeServer2 text-mining software, developed by Spain’s Bioalma.
 
The deal was the second agreement for the software since it was upgraded in the fall, and caps a year of double-digit growth for Active Motif’s other informatics business, TimeLogic.
 
Chris Hoover, marketing manager for the TimeLogic group, told BioInform via e-mail that sales of TimeLogic products grew by 12 percent in 2006, “and have demonstrated substantial growth since our acquisition by Active Motif in 2003.”
 
Hoover said that TimeLogic has benefited from Active Motif’s marketing strength. “With expanded marketing and distribution channels, we are better able to reach bioinformaticists as well as biologists that rely heavily on genomics data for their research,” he said.
 
While the privately held firm does not disclose revenue figures, Hoover said that a key growth driver has been strong adoption of the company’s flagship DeCypher accelerated bioinformatics platform in Europe, as well as healthy sales of its CodeQuest desktop biocomputing workstation, which the company launched in 2005 to target end-user biologists.
 
CodeQuest includes an FPGA-based DeCypher accelerator in a 2-CPU dual core desktop workstation and is priced under $25,000 for academic users. Hoover said that it is “the most affordable TimeLogic product ever released,” which has “simplified resource planning and purchase approval for many US government labs and academic genomics cores.”
 
In addition to launching CodeQuest in 2005, Active Motif also expanded its bioinformatics capabilities that year when it began distributing Bioalma’s AKS.
 
In January, Active Motif announced that Siena Biotech had extended an existing license for AKS2, and this week the company announced that TGen is using the software to help analyze siRNA screening data.
 
Jeff Kiefer, head of the knowledge mining lab in TGen’s pharmaceutical genomics division, told BioInform that his group is primarily using the software to interrogate lists of genes that result from high-throughput siRNA screens. He said that AKS2 offers “deep data coverage” and a set of user-friendly network analysis and visualization tools.
 
Kiefer said that the TGen knowledge-mining group also uses Ariadne Genomics’ MedScan Reader text-mining technology, but more for its network-building capability as part of Ariadne’s broader PathwayStudio platform. “They both bring different aspects” to literature mining, he said.
 
Active Motif plans to expand its informatics portfolio with an upcoming product called PipeWorks, a drag-and-drop workflow interface for CodeQuest that Hoover said will be available “soon.”
 
In addition, Active Motif is “actively pursuing” the burgeoning next-generation sequence-analysis market, Hoover said, adding that customers are currently using TimeLogic products to analyze sequencing data generated by 454 Life Sciences’ and other platforms. “We feel strongly that our efficient, space-saving FPGA technology will help address the computational goals of the $1,000 genome.”
 
One of the earliest players in accelerated bioinformatics, TimeLogic now shares the market with a growing number of companies developing FPGA technology for life science applications, including Mitrionics, CLC Bio, Progeniq, and Adaptive Genomics.
 
Hoover noted, however, that many of these new products are “geared towards engineers and parallel programming experts, while others are limited in their search scope.”
 
In addition, he said, the demand for accelerated systems should continue to grow even as new players enter the market.
 
“Increased data growth, higher power costs, and broader adoption of genomics techniques by research scientists will increase demand for efficient biocomputing platforms,” he said. “With the debut of low-cost sequencing technologies, millions of novel sequences are being added to the public domain. At the same time, funding shortages and higher energy costs place increased burdens on genome annotation and database curation projects to be highly cost-effective.”

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