Massively Parallel Phylogeny Reconstruction for the Age of DNA Big Data
Lead Research Organisation:
University of Edinburgh
Department Name: Sch of Biological Sciences
Abstract
How are species related? This question, of fundamental importance across life sciences, can in principle be addressed using DNA sequence data. Implicit in these data is the pattern of relationships of the species the DNA came from, known as their phylogeny, usually represented as a tree. However, algorithms and software to reconstruct phylogenetic trees for very large input are lagging behind the recent explosion in the availability of DNA sequence data.
The goal of this project is to create parallel algorithms and open-source software for reconstructing large phylogenies by heuristic searches suited to very large data.
The project will use theoretical and computational approaches. These will include use and characterisation of nature-inspired advanced heuristics (e.g. Strobl and Barker 2016), programming and use of massively parallel computer systems, optimisation of algorithms and implementations, and cross-site, distributed machine learning techniques.
The goal of this project is to create parallel algorithms and open-source software for reconstructing large phylogenies by heuristic searches suited to very large data.
The project will use theoretical and computational approaches. These will include use and characterisation of nature-inspired advanced heuristics (e.g. Strobl and Barker 2016), programming and use of massively parallel computer systems, optimisation of algorithms and implementations, and cross-site, distributed machine learning techniques.
Organisations
People |
ORCID iD |
Daniel Barker (Primary Supervisor) | |
Joseph Guscott (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/R513209/1 | 01/10/2018 | 30/09/2023 | |||
2114792 | Studentship | EP/R513209/1 | 01/10/2018 | 30/09/2022 | Joseph Guscott |