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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Vydané v:	Journal of applied statistics Ročník 52; číslo 12; s. 2321 - 2353
Hlavný autor:	Dai, Wanyang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	England Taylor & Francis 10.09.2025 Taylor & Francis Ltd
Predmet:	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
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