NeuralNetworkModel

A function to train an artificial neural network model to classify medulloblastoma subgroups using DNA methylation beta values (Illumina Infinium HumanMethylation450). Prediction is followed by training if new data is provided.

Utilizing a combination of machine learning models (Random Forest, Naive Bayes, K-Nearest Neighbor, Support Vector Machines, Extreme Gradient Boosting, and Linear Discriminant Analysis) and a deep Artificial Neural Network model, 'MBMethPred' can predict medulloblastoma subgroups, including wingless (WNT), sonic hedgehog (SHH), Group 3, and Group 4 from DNA methylation beta values. See Sharif Rahmani E, Lawarde A, Lingasamy P, Moreno SV, Salumets A and Modhukur V (2023), MBMethPred: a computational framework for the accurate classification of childhood medulloblastoma subgroups using data integration and AI-based approaches. Front. Genet. 14:1233657. <doi: 10.3389/fgene.2023.1233657> for more details.

Edris Sharif Rahmani

MBMethPred

Medulloblastoma Subgroups Prediction

Ankita Sunil Lawarde

Vijayachitra Modhukur

NeuralNetworkModel function

<dl><dt>Epochs</dt>
<dd>The number of epochs.</dd>
<dt>NewData</dt>
<dd>A methylation beta values input from the ReadMethylFile function.</dd>
<dt>InstallTensorFlow</dt>
<dd>Logical. Running this function for the first time, you need to install TensorFlow library (V 2.10-cpu). Default is TRUE.</dd></dl>

Arguments

Artificial neural network model — NeuralNetworkModel

<dl>

<dt>Epochs</dt>
<dd>The number of epochs.</dd>


<dt>NewData</dt>
<dd>A methylation beta values input from the ReadMethylFile function.</dd>


<dt>InstallTensorFlow</dt>
<dd>Logical. Running this function for the first time, you need to install TensorFlow library (V 2.10-cpu). Default is TRUE.</dd>

</dl>

NeuralNetworkModel: Artificial neural network model

Description

Value

Arguments

Examples