Eureka! Student creates free online software for genetics research
Sagi Abelson's Eureka-DMA program gives a graphical representation of gene test results.
A Ph.D. student at Technion-Israel Institute of Technology has come up with an inexpensive solution that could help speed up the development of genetic research.
Earlier this year, Sagi Abelson released a software program called Eureka-DMA. This free graphical interface can be used by geneticists to speed up the types of genetic examinations that can reveal new genes and genetic diseases, or help with the development of new medications.
The program takes the huge amounts of data generated by DNA microarray analysis – which normally looks like a bunch of columns of numbers and letters and includes thousands of data points – and turns it into a graphical representation. Along the way, it uses statistical protocols to normalize the results and filter out non-relevant data. Researchers can then explore the genetics in various ways, including a "heat map," which shows genes that have either high or low expressions. Results can also be compared to existing gene databases so researchers can see what the genetic components mean.
Abelson's system was first described in February in the journal BMC Bioinformatics. The advantage of Eureka-DMA, he said, is that biologists can look at the results of their genetic tests without the assistance of a bioinformatician, a specialist who focuses on using software to store, organize and analyze genetic data. "Eureka-DMA combines simplicity of operation and ease of data management with the rapid execution of multiple task analyses," Abelson said. "This ability can help researchers who have less experience in bioinformatics to transform the high throughput data they generate into meaningful and understandable information."
Eureka-DMA is not alone; at least eight other software systems perform some similar functions. A recent paper in the International Journal of Computer Science and Business Informatics examined them all and found that Abelson's software was a basic tool in some aspects, but that its visualization tools excelled compared to other systems. The paper in particular called out Eureka-DMA's heat map, saying it helped users to better understand gene-expression data.
Abelson has already put his software to good use himself. His doctoral research thesis used Eureka-DMA to study ovarian cancer cell populations.
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