Prediction of disease-disease associations based on relation extraction from biomedical journals using support vector machines
Predicting novel associations between biomedical entities, such as genes, drugs and diseases, can suggest new topics for experiments and new insights in drug design. Due to the massive amounts of relevant data available, a computational approach is well-suited for this task. Initial data can be take...
Saved in:
Main Author: | Laron, Andrew V. |
---|---|
Format: | text |
Language: | English |
Published: |
Animo Repository
2017
|
Subjects: | |
Online Access: | https://animorepository.dlsu.edu.ph/etd_masteral/5765 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | De La Salle University |
Language: | English |
Similar Items
-
Time-Series Link Prediction Using Support Vector Machines
by: Fernandez, Proceso L, Jr, et al.
Published: (2017) -
Link Prediction in a Weighted Network Using Support Vector Machine
by: Co, Jan Miles, et al.
Published: (2016) -
Web taxonomy integration using support vector machines
by: Zhang, D., et al.
Published: (2013) -
Prediction of antifungal activity with support vector machine
by: Li, Z.-R., et al.
Published: (2014) -
Splice Site Prediction Using Support Vector Machines with a Bayes Kernel
by: ZHANG, Ya, et al.
Published: (2006)