Detection of functional and topological modules in protein interaction networks
Mapping the complete set of protein and gene interactions in the human cell has been a goal of the biological community for nearly two decades, since the first human genome was sequenced. To this end, computational approaches have been studied in depth to allow functional annotation of protein inter...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Final Year Project |
| Language: | English |
| Published: |
2018
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/10356/73997 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Mapping the complete set of protein and gene interactions in the human cell has been a goal of the biological community for nearly two decades, since the first human genome was sequenced. To this end, computational approaches have been studied in depth to allow functional annotation of protein interactions. In this project, we explored the potential of using four common module detection algorithms - stochastic block model, Louvain method, modified Louvain (incremental Louvain) method and link community - in order to detect functional modules of for protein interaction networks. We implemented these algorithms in a Cytoscape application for users to run on their respective networks. Using this application, we conducted a comparative study of the algorithms to understand their applicability in protein function annotation and determine how close topological modules of protein-interaction networks are to their functional modules. |
|---|