Prediction of antimicrobial peptides using hyperparameter optimized support vector machines
Philosophiae Doctor - PhD === Antimicrobial peptides (AMPs) play a key role in the innate immune response. They can be ubiquitously found in a wide range of eukaryotes including mammals, amphibians, insects, plants, and protozoa. In lower organisms, AMPs function merely as antibiotics by permeabiliz...
Main Author: | Gabere, Musa Nur |
---|---|
Other Authors: | Vladimir, Bajic |
Language: | en |
Published: |
University of the Western Cape
2014
|
Subjects: | |
Online Access: | http://hdl.handle.net/11394/2633 |
Similar Items
-
Support Vector Machine Ensemble Based on Feature and Hyperparameter Variation.
by: WANDEKOKEN, E. D.
Published: (2016) -
Anti-Fibrotic Activity of an Antimicrobial Peptide in a Drosophila Model
by: Dilan Khalili, et al.
Published: (2021-05-01) -
Assessing the behavior of machine learning methods to predict the activity of antimicrobial peptides
by: Francy Liliana Camacho, et al.
Published: (2016-12-01) -
mACPpred: A Support Vector Machine-Based Meta-Predictor for Identification of Anticancer Peptides
by: Vinothini Boopathi, et al.
Published: (2019-04-01) -
Simulated annealing driven pattern search algorithms for global optimization
by: Gabere, Musa Nur
Published: (2008)