CNN-Promoter, new consensus promoter prediction program based on neural networks
A new promoter prediction program called CNN-Promoter is presented. CNN-Promoter allows DNA sequences to be submitted and predicts them as promoter or non-promoter. Several methods have been developed to predict the promoter regions of genomes in eukaryotic organisms including algorithms based on Ma...
- Autores:
-
Bedoya, O. (Óscar)
Bustamante, S. (Santiago)
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2011
- Institución:
- Universidad EIA .
- Repositorio:
- Repositorio EIA .
- Idioma:
- eng
- OAI Identifier:
- oai:repository.eia.edu.co:11190/165
- Acceso en línea:
- https://repository.eia.edu.co/handle/11190/165
- Palabra clave:
- REI00157
PERCEPTRONES
PERCEPTRONS
INTELIGENCIA ARTIFICIAL
ARTIFICIAL INTELLIGENCE
TECNOLOGÍAS PARA LA SALUD
TECHNOLOGY IN HEALTH
PROMOTER PREDICTION
NEURAL NETWORKS
CONSENSUS STRATEGY
PREDICCIÓN DE PROMOTORES
REDES NEURONALES
ESTRATEGIA DE CONSENSO
- Rights
- openAccess
- License
- Derechos Reservados - Universidad EIA, 2020
| Summary: | A new promoter prediction program called CNN-Promoter is presented. CNN-Promoter allows DNA sequences to be submitted and predicts them as promoter or non-promoter. Several methods have been developed to predict the promoter regions of genomes in eukaryotic organisms including algorithms based on Markov’s models, decision trees, and statistical methods. Although there are plenty of programs proposed, there is still a need to improve the sensitivity and specificity values. In this paper, a new program is proposed; it is based on the consensus strategy of using experts to make a better prediction. The consensus strategy is developed by using neural networks. During the training process, the sensitivity and specificity were 100 % and during the test process the model reaches a sensitivity of 74.5 % and a specificity of 82.7 %. |
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