Algorithms for Predictive Plant Monitoring

Term: 
2019-2020 Summer
Faculty Department of Project Supervisor: 
Faculty of Engineering and Natural Sciences
Number of Students: 
2

In this project we perform data analysis and design a predictive algorithm for various plant species. This project starts with data management to understand the nature of a trait under given environmental conditions. Predictive algorithms will explain the reaction strategy of a species under changing environmental conditions. Data will be later combined with the genome information of the species of interest for identifying candidate genes associated with the trait of interest. Requirements: Having experience on a data management and algorithm writing software and/or computing languages (such as Matlab, C++, R, linux, SPSS, Python, or Excel). Having passed a Genetics course.

Related Areas of Project: 
Computer Science and Engineering
Molecular Biology, Genetics and Bioengineering
Electronics Engineering