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Bioinformatics Applications Based On Machine Learning
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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.
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Keywords
- 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
- Metabolism
- Metagenomics
- metrics
- mitochondrial protein
- Parameter estimation
- part
- particle swarm optimization
- Personality assessment
- plasmodium falciparum
- power management
- real-life patients
- régression
- Swarm intelligence
- Technology, engineering, agriculture
- Technology: general issues
- transposable elements
- Video Analysis
- Weka
- Yeast
Links
DOI: 10.3390/books978-3-0365-0761-3Editions