Since the discovery of the first plant virus, plant virus universe has been always expanding at an ever-increasing rate. However, it is now becoming clearer that the more we know about virus diversity the more we understand this is only part of the picture: many more undiscovered viruses are hiding behind the carpet of unknown. I believe that recent advances in the field of Machine learning can help with getting much of the hidden viral diversity back to the daylight. In my individual project I aspire to use state-of-the-art machine learning approaches to achieve new heights in detecting known and unknown viruses.
During this project I hope to work on many things. Here are some of them:
- Development of the virus detection method for plant-virus metagenomic sequencing data, which would outperform existing methods.
- Refining this method to be accurate, time-efficient and capable of novel virus detection.
- Assessment of the developed method on a variety of plant viromes.
- Development of an easy-to-use pipeline, which would include the developed method, and active promotion of it in the scientific community.