Systems Biology in Ecology & Agriculture
The key motivation underlying the research in the group is the development of data-guided strategies for the educated design of indigenous communities in agro-ecosystems.
To this end, we apply and develop computational models for predicting and understanding the networks of interactions formed within microbial communities by analyzing meta/genomics data. Using our tools we can delineate trophic dependencies, exchanges, competitive and cooperative interactions within natural microbial communities and use simulations for predicting potential routes for the optimization of predefined functions.
Our research projects demonstrate the application of metabolic network approaches for the analysis of genomic and metagenomics data in agricultural systems toward the development of sustainable practices.
Research projects include:
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Modeling based design of soil amendments that lead to enhanced biodegradation of soil pollutants including BTEX and herbicides
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Deciphering microbial functions in soil communities towards the development of sustainable solutions for suppression of soil-borne disease
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Developing ('omic) data-guided strategies for the reducing post-harvest pathology
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Management of greenhouse gas emissions in natural and artificial systems
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Development of new tools for the functional analysis of microbial interactions
An illustration of the work process we envision is described in Ginatt et. al..
Network is calling? Come and join us!
From the BARD newsletter, watch the video explaining how we use metagenomics for reducing unpredictability in soil amendment research to benefit agricultural crops.
Watch the lecture held for Volcani Center 100 years anniversary event (Hebrew):
Genomics in the service of agriculture and the environment.
Listen to the podcast (Hebrew)
Wrote on us:
Microbial design: Microbial Consortium Design Benefits from Metabolic Modeling.
Dr. Kusum Dhakar presents her work and vision.
Projects we take part in:
Model Farm for Sustainable Agriculture.
