Feature selection and ensemble of regression models for predicting the protein macromolecule dissolution profile
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86092529" target="_blank" >RIV/61989100:27240/14:86092529 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/14:86092529
Result on the web
<a href="http://dx.doi.org/10.1109/NaBIC.2014.6921864" target="_blank" >http://dx.doi.org/10.1109/NaBIC.2014.6921864</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/NaBIC.2014.6921864" target="_blank" >10.1109/NaBIC.2014.6921864</a>
Alternative languages
Result language
angličtina
Original language name
Feature selection and ensemble of regression models for predicting the protein macromolecule dissolution profile
Original language description
Predicting the dissolution rate of proteins plays a significant role in pharmaceutical/medical applications. The rate of dissolution of Poly Lactic-co-Glycolic Acid (PLGA) micro- and nanoparticles is influenced by several factors. Considering all factorsleads to a dataset with three hundred features, making the prediction difficult and inaccurate. Our present study consists of three phases. Firstly, dimensionality reduction techniques are applied in order to simplify the task and eliminate irrelevant and redundant attributes. Subsequently, a heterogeneous pool of several classical regression algorithms is created and evaluated. Regression algorithms in the pool are independently trained to identify the problem at hand. Finally, we test several ensemble methods in order to elevate the accuracy of the prediction. The Evolutionary Weighted Ensemble methodproposed in this paper offered the lowest RMSE and significantly outperformed competing classical algorithms and other ensemble techniq
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
—
Result continuities
Project
—
Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
NaBIC 2014 ; CASoN 2014 : July 30-31, Porto, Portugal
ISBN
978-1-4799-5937-2
ISSN
—
e-ISSN
—
Number of pages
6
Pages from-to
121-126
Publisher name
IEEE
Place of publication
New York
Event location
Porto
Event date
Jul 30, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—