Project information
- Category: Web Development
- Client: The Australian National University
- Project date: Aug. 15, 2019
- Project URL: https://plantpredict.shinyapps.io/PredictionShiny/
Wheat Physiology Predictor
Research assistant (part time) at the ARC Centre of Excellence for Translational Photosynthesis in the Research School of Biology, ANU.
Duties involved: collecting data in the field from plants such as wheat and barley, analysing data with machine learning and data modelling by using R studio and Python, and helping with constructing and refurbishing the web server with the R shiny app.
Some of the work is referred to my Research Publications, such as a web app called Wheat Physiology Predictor (shinyapps.io), which allows users to upload the csv file to the shiny web interface and obtain the data predicted by a backend server running with Python (http protocol).
Due to the large latency by using shinyapp.io, I had also dockerised all the R codes in a container and hosted in a new temporary address: Wheat Physiology Predictor