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Compugen, Tel Aviv University announce unique method for alternative splicing
TEL AVIV, Israel—Compugen Ltd. and Tel Aviv University announced in late fall the development of a new method for identifying alternative splicing without the need for either EST (Expressed Sequence Tag) data or microarray experimentation.
The novel method is based on a computer-learning model incorporating algorithms reflecting
Compugen's understanding of the process of alternative splicing.
The work was a collaborative effort between Compugen's scientists and Professors Ron Shamir and Gil Ast from Tel Aviv University.
Currently, the two most common methods for identifying alternative splicing rely on mining
substantial experimental data, either EST libraries or microarray results. Compugen's method, which is based on comparative genomics, can accurately predict alternative splicing based solely on human and mouse genomic DNA.
Using the model, Compugen has discovered over 300 novel predicted splice variants. As this was an initial application of the computer-learning model, hundreds more novel splice variants are expected to emerge in the future.
"This development is another example of the research that is done at Compugen, relying on proprietary predictive modeling and experimental validation rather than high-throughput experimental approaches. The early use of this splice variant model has already increased our collection of potential therapeutic proteins and diagnostic markers beyond that which was possible with our industry leading EST-based LEADS predictive model," says Mor Amitai, Ph.D., President and Chief Executive Officer of Compugen Ltd.