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Bioinformatics Applications Based On Machine Learning



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Autore: Chamoso Pablo Visualizza persona
Titolo: Bioinformatics Applications Based On Machine Learning Visualizza cluster
Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica: 1 online resource (206 p.)
Soggetto topico: Technology: general issues
Soggetto non controllato: Affective Computing
Arabidopsis thaliana
Artificial Neural Networks
bi-directional LSTM
bioinformatics
biological functions detection
classification
clinical data
clinical implications
cluster
computer vision
convolutional neural network
CTX-M
data mining
Decision table
deep learning
derivative-free optimization
detection
diabetes
dynamic models
ear detection
epidemiology
evolutionary computation
evolutionary computing
feature selection
forecast
fuel cell
gene clustering
genetic programming
glycolysis
gradient boosting
Harmony Search
hybrid systems
hydrogen energy
image recognition
informative genes
intelligent systems
machine learning
Machine Learning
metabolism
metagenomics
metrics
mitochondrial protein
parameter estimation
PART
Particle Swarm Optimization
personality assessment
plasmodium falciparum
power management
real-life patients
regression
swarm intelligence
transposable elements
video analysis
Weka
yeast
Persona (resp. second.): RodriguezSara
MohamadMohd
González-BrionesAlfonso
ChamosoPablo
Sommario/riassunto: The great advances in information technology (IT) have implications for many sectors, such as bioinformatics, and has considerably increased their possibilities. This book presents a collection of 11 original research papers, all of them related to the application of IT-related techniques within the bioinformatics sector: from new applications created from the adaptation and application of existing techniques to the creation of new methodologies to solve existing problems.
Titolo autorizzato: Bioinformatics Applications Based On Machine Learning  Visualizza cluster
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910674055503321
Lo trovi qui: Univ. Federico II
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