What Modern Technology Can Teach Us About Nature
About This Project
by: Dr. Anjali Sheahan – Computational Biology Scientist at Invaio
✓ Machine Learning
✓ Deep Learning
✓ Artificial Intelligence
✓ Computational Analysis
I have always been passionate about translational research. In the past, the pursuit of my work has been to advance targeted therapies. What brought me to Invaio was the opportunity to work on projects in a different area that would be both technically challenging and highly impactful. With my background in computational biology, target identification, and assay development – I saw a chance to bring this life sciences expertise to other biological systems.
Computational biology greatly empowers the work my team does at Invaio. We take a data-driven approach to experiments we do which informs and predicts experimental outcomes, and enables more efficient use of resources. Furthermore, we use data mining, systems modeling, and machine learning methods to help us develop strategies that are more likely to yield actives that selectively inhibit pathogens, without disrupting the complex biological system that they are a part of. This philosophy really appealed to me.
We are working to selectively disrupt the pathogen, and do this with naturally occurring molecules.
At Invaio Sciences, as we work to fight crop disease, control insect pests and enhance the health of beneficial insects, we don’t just look at the single species we are working on but the system as a whole.
As an example, we not only consider a pathogen by itself but also the living organism a pathogen might be causing disease in, the living organism that transmits the pathogen, and the living organism from which the pathogen originated. Beyond this, we also consider that the pathogenic bacteria, and each of these organisms are components of a diverse system that also contain beneficial bacteria, insects, plants, and animals (including humans).
Our experience with this data-driven approach has proven it to be rewarding and impactful. It has been personally fulfilling to be in an open-minded, supportive, and intellectually-stimulating environment that values these novel methodologies. I am confident that culture that we strive for, that is enthusiastic to adopt new ideas and technologies, will continue to pave the way to success for Agriculture in the future.
Anjali Sheahan, Ph.D. is a computational biologist with extensive experience in bioinformatics, statistics, assay development, and imaging. Anjali joined Invaio after many years of academic cancer research at the Dana-Farber Cancer Institute and the Molecular Imaging Program at Stanford University. In her spare time, Anjali enjoys reading, dancing badly, and spending time with family.