The first article in this series will introduce perceptrons and the adaline (ADAptive LINear NEuron), which fall into the category of single-layer neural networks. The perceptron is not only the first algorithmically described learning algorithm [1], but it is also very intuitive, easy to impleme...
The first article in this series will introduce perceptrons and the adaline (ADAptive LINear NEuron), which fall into the category of single-layer neural networks. The perceptron is not only the first algorithmically described learning algorithm [1], but it is also very intuitive, easy to impleme...
To build the chronological age predictor, we developed a novel multi-view graph-level representation learning (MGRL) algorithm that fuses a deep graph convolutional neural network (GCN) called DeeperGCN39 with a more traditional multi-layer perceptron (MLP) (Methods, Figs. 1b and 2a), the goa...
5d). The intestinal barrier comprises a thick mucus layer with antimicrobial products, a layer of intestinal epithelial cells and a layer of mesenchymal cells, dendritic cells, lymphocytes and macrophages54. As such, these five cell types are expected to yield high predictive ability. Moreover, ...
In our study, we employ a neural network framework that integrates an Autoencoder (AE) with a Multi-layer Perceptron (MLP) regressor. This hybrid model can assign multi-mapping reads to specific TE loci, a crucial step in quantifying TE expression in individual cells. The process begins by ...
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Single-cell transcriptomics (SCT) sequencing technology enables the simultaneous measurement of thousands of genes in cells [5,6,7]. In addition to gene expression, the data usually also contain additional characteristics such as cell type. Since different cell types have different gene expression pro...
[251] adopts multiple-layer perceptron bagging to identify regulons, DeepDRIM [252] utilizes supervised deep neural network to reconstruct gene regulatory networks. In particular, DeepDRIM is shown to be tolerant to dropout events in scRNA-seq and identify distinct regulatory networks of B cells ...
We found that the trained classifiers yield comparable AUROC scores and we selected the multi-layer perceptron (MLP) as the optimal one, based on its superior performance on the training dataset in 5-fold cross validation (Additional file 1: Fig. S4A). We compared the performance of our train...
We trained a Multi-layer Perceptron (MLP) classifier using the annotated representatives’ cells and used it to predict the cell types of the rest of the non-representative samples’ cells generated by the deep learning model. As shown in Fig. 2b, cell clustering remains intact in the semi-...