|Project's title||Approximation algorithms in two bioinformatics problems: DNA motif finding and ARG inference|
|Research hosting institution||Institute of Information Technology|
|Project leader’s name||Nguyen Thi Phuong Thao|
|Project duration||01/01/2019 - 31/12/2020|
|Project’s budget||500 million VND|
|Goal and objectives of the project||
Researching and developing approximation algorithms to solve two bioinformatics problems: (1) DNA motif finding, and (2) ARG inference.
|Main results|| |
- We proposed the GAMARG algorithm that combined the four-gamete test constraint with the longest shared ends strategy in ARG4WG to optimize the number of recombination events in ARG building process. Experiment with different datasets showed that GAMARG algorithm outperforms other heuristic algorithms in building ARGs for large datasets. It also is much better than other heuristic algorithms and comparable to exhaustive search methods for small datasets.
|Novelty and actuality and scientific meaningfulness of the results|| |
We proposed an ARG inference algorithm that was able to handle thousands sequences with tens of thousands of markers, and also could reach the minimum recombination ARGs. Besides, this is the first large-scale study to investigate multiple CYP genes in the KHV for precision medicine from a public health perspective. Differences found in the distributions of metabolizers for the KHV suggest careful prescriptions for CYP2C19 and CYP3A5-metabolized drugs.
|Products of the project|| |
- Scientific papers in referred journals (list):
|Images of project|| |