Gene mutation estimations via mutual information and Ewens sampling based CNN & machine learning algorithms

We conduct gene mutation rate estimations via developing mutual information and Ewens sampling based convolutional neural network (CNN) and machine learning algorithms. More precisely, we develop a systematic methodology through constructing a CNN. Meanwhile, we develop two machine learning algorith...

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Veröffentlicht in:	Journal of applied statistics Jg. 52; H. 12; S. 2321 - 2353
1. Verfasser:	Dai, Wanyang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England Taylor & Francis 10.09.2025 Taylor & Francis Ltd
Schlagworte:	Algorithms Artificial neural networks convolutional neural network (CNN) Ewens sampling Gene mutation rate Gene sequencing Genetic modification Kuhn-Tucker method Machine learning multi-input multi-output (MIMO) mutual information Mutation Optimization Optimization techniques Proteins Sampling stochastic gradient multi-input multi-output (MIMO) mutual information Ewens sampling stochastic gradient Gene mutation rate convolutional neural network (CNN) machine learning
ISSN:	0266-4763, 1360-0532
Online-Zugang:	Volltext
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