Biography
Jana is an Australian Research Council (ARC) DECRA (Discovery Early Career Researcher Award) fellow at the Australian National University in Canberra, Australia. She is a bioinformatician who uses computational techniques to drive knowledge discovery in plant sciences. She is particularly interested in the interactions between plants and their pathogens and has released several widely-used software tools for fungal effector prediction using machine learning.
Jana completed an MSc in Computer Science with a focus on Bioinformatics at the University of Freiburg, Germany. In 2008, she commenced a PhD at the University of Western Australia (Crawley, WA, Australia) in which she developed novel methods for the computational prediction of noncoding RNA structure. In 2012, she joined the Commonwealth Scientific and Industrial Research Organization (CSIRO) as a Postdoctoral Fellow to work on plant–pathogen interactions and genomics. In 2018, she joined the Australian National University as an ARC DECRA fellow to uncover how rust fungi cause devastating plant diseases. Her current research interests include plant–pathogen interactions, the application of machine learning to protein function prediction and genomics for elucidating biological function. Jana is an accredited Software Carpentry instructor and is passionate about collaborative, reproducible and inclusive science.
Event Abstracts
New Phytologist Now
New Phytologist Now
Machine learning in plant–pathogen interactions: empowering biological predictions from field scale to genome scale
- 7 December 2022 - GMT
Machine learning in plant–pathogen interactions: empowering biological predictions from field scale to genome scale
Jana Sperschneider
CSIRO
Machine learning (ML) encompasses statistical methods that learn to identify patterns in complex datasets. Here, Jana reviews application areas in plant–pathogen interactions that have recently benefited from ML. She provides an under-the-hood glance into her developed suite of ML-based tools for pathogen effector prediction such as EffectorP. Jana will discuss common pitfalls and challenges she encountered during the development of ML approaches. Finally, she will highlight future opportunities for ML as a tool for dissecting plant–pathogen interactions, for example through integration of AlphaFold predictions or ML-driven effector gene annotation.
The New Phytologist Tansley Medal 2018 – Liana Burghardt and Jana Sperschneider
Sarah Lennon, Liam Dolan
Machine learning in plant–pathogen interactions: empowering biological predictions from field scale to genome scale
Jana Sperschneider
Jana Sperschneider
