Evogene to Present at Crops and Chemicals 2016 Conference

CSO Dr. Eyal Emmanuel to Present Initial Results from Insect Control Novel Toxin Discovery Program
July 13, 2016
Evogene to Present at Crops and Chemicals 2016 Conference (Enlarge)

Rehovot, Israel – July 13, 2016 - Evogene Ltd. (NYSE, TASE: EVGN), a leading biotechnology company for the improvement of crop productivity, today announced that its Chief Scientific Officer, Dr. Eyal Emmanuel, will present initial results from the Company’s Insect Control Novel Toxin Discovery Program at the Crops and Chemicals Conference taking place July 19 - 21, 2016 in Raleigh, North Carolina. Dr. Emmanuel’s presentation is scheduled for July 20th at 11:30am in the Plant Biotechnology stream of the conference.


At his presentation, Dr. Emmanuel will describe Evogene’s unique approach for the discovery of microbial genes demonstrating insecticidal activity with novel 'mode of action' and will present preliminary results for certain selected genes.  The genes for which preliminary results will be provided include genes discovered from cultured bacteria as part of Evogene's program with Marrone Bio Innovations Inc. (NASDAQ: MBII), as well as genes discovered from its proprietary, experiments incorporating metagenomics data. The candidate genes from both sources were discovered using the Company's in silico algorithmic approach. Validation of the insecticidal activity for such genes included diet-based assays against several key target insects, demonstrating strong support for the unique methodologies utilized in Evogene's Insect Control Program.


Evogene's in silico approach for novel toxin discovery leverages two key proprietary technologies –  comprehensive integrated databases, and a dedicated computational analysis platform (BiomeMinerTM). The integrated databases are enriched with microbial genes consisting of insecticidal activity from both cultured and uncultured bacteria (metagenomics), sourced from proprietary and public experiments. The BiomeMinerTM computational platform utilizes advanced algorithms and machine learning technologies, and has been designed to sift through many millions of genes and pinpoint the most promising candidates to yield potential novel insecticidal modes of action.

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