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Bioinformatics Applications Based On Machine Learning

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.

This book is included in DOAB.

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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/books978-3-0365-0761-3

Editions

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