Bioinformatics Applications Based On Machine Learning
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...
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Format: | Electronic Book Chapter |
Language: | English |
Published: |
Basel, Switzerland
MDPI - Multidisciplinary Digital Publishing Institute
2021
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Online Access: | DOAB: download the publication DOAB: description of the publication |
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072 | 7 | |a TB |2 bicssc | |
100 | 1 | |a Chamoso, Pablo |4 edt | |
700 | 1 | |a Rodriguez, Sara |4 edt | |
700 | 1 | |a Mohamad, Mohd |4 edt | |
700 | 1 | |a González-Briones, Alfonso |4 edt | |
700 | 1 | |a Chamoso, Pablo |4 oth | |
700 | 1 | |a Rodriguez, Sara |4 oth | |
700 | 1 | |a Mohamad, Mohd |4 oth | |
700 | 1 | |a González-Briones, Alfonso |4 oth | |
245 | 1 | 0 | |a Bioinformatics Applications Based On Machine Learning |
260 | |a Basel, Switzerland |b MDPI - Multidisciplinary Digital Publishing Institute |c 2021 | ||
300 | |a 1 electronic resource (206 p.) | ||
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338 | |a online resource |b cr |2 rdacarrier | ||
506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
520 | |a 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. | ||
540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |4 https://creativecommons.org/licenses/by/4.0/ | ||
546 | |a English | ||
650 | 7 | |a Technology: general issues |2 bicssc | |
653 | |a machine learning | ||
653 | |a metagenomics | ||
653 | |a bioinformatics | ||
653 | |a CTX-M | ||
653 | |a data mining | ||
653 | |a cluster | ||
653 | |a clinical implications | ||
653 | |a diabetes | ||
653 | |a epidemiology | ||
653 | |a forecast | ||
653 | |a PART | ||
653 | |a Decision table | ||
653 | |a Weka | ||
653 | |a real-life patients | ||
653 | |a regression | ||
653 | |a ear detection | ||
653 | |a computer vision | ||
653 | |a convolutional neural network | ||
653 | |a image recognition | ||
653 | |a video analysis | ||
653 | |a gene clustering | ||
653 | |a swarm intelligence | ||
653 | |a biological functions detection | ||
653 | |a informative genes | ||
653 | |a fuel cell | ||
653 | |a hydrogen energy | ||
653 | |a intelligent systems | ||
653 | |a hybrid systems | ||
653 | |a Artificial Neural Networks | ||
653 | |a power management | ||
653 | |a Machine Learning | ||
653 | |a personality assessment | ||
653 | |a gradient boosting | ||
653 | |a Affective Computing | ||
653 | |a transposable elements | ||
653 | |a metrics | ||
653 | |a deep learning | ||
653 | |a detection | ||
653 | |a classification | ||
653 | |a mitochondrial protein | ||
653 | |a bi-directional LSTM | ||
653 | |a plasmodium falciparum | ||
653 | |a Particle Swarm Optimization | ||
653 | |a Harmony Search | ||
653 | |a parameter estimation | ||
653 | |a Arabidopsis thaliana | ||
653 | |a clinical data | ||
653 | |a feature selection | ||
653 | |a genetic programming | ||
653 | |a evolutionary computation | ||
653 | |a dynamic models | ||
653 | |a evolutionary computing | ||
653 | |a derivative-free optimization | ||
653 | |a metabolism | ||
653 | |a glycolysis | ||
653 | |a yeast | ||
856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/3940 |7 0 |z DOAB: download the publication |
856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/76494 |7 0 |z DOAB: description of the publication |