Comparing artificial neural networks, general linear models and support vector machines in building predictive models for small interfering RNAs.
<h4>Background</h4>Exogenous short interfering RNAs (siRNAs) induce a gene knockdown effect in cells by interacting with naturally occurring RNA processing machinery. However not all siRNAs induce this effect equally. Several heterogeneous kinds of machine learning techniques and feature...
Enregistré dans:
Auteurs principaux: | Kyle A McQuisten, Andrew S Peek |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Public Library of Science (PLoS)
2009
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/54a6ebf42aa84d0aa39f142f1ab115e5 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Hybrid Machine Learning Model for Body Fat Percentage Prediction Based on Support Vector Regression and Emotional Artificial Neural Networks
par: Solaf A. Hussain, et autres
Publié: (2021) -
Carrot Sorting Based on Shape using Image Processing, Artificial Neural Network, and Support Vector Machine
par: A Jahanbakhshi, et autres
Publié: (2019) -
Small interfering RNAs (siRNAs) in cancer therapy: a nano-based approach
par: Mahmoodi Chalbatani G, et autres
Publié: (2019) -
Performance evaluation of linear discriminant analysis and support vector machines to classify cesarean section
par: Abdul Azis Abdillah, et autres
Publié: (2021) -
Hourly Energy Consumption Forecasting for Office Buildings Based on Support Vector Machine
par: XIAO Ran, et autres
Publié: (2021)