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Ibex BCR Deep Encoders

Authors: Borcherding, Nicholas;

Ibex BCR Deep Encoders

Abstract

Ibex This is a series of 72 Keras3-based amino acid encoders for Heavy and Light chains of the B cell Receptor (BCR). These are the individual trained models for larger Ibex package that will be available after review from BioConductor. The package itself has the functionality to employ these models and interact with single-cell data, but due to the size of the trained models, the keras objects are stored here.Sequence inputs Human Heavy: 10000000 Human Light: 5000000 Human Heavy-Expanded: 5000000 Human Light-Expanded: 2500000 Mouse Heavy: 5000000 Mouse Heavy-Expanded: 5000000 Model details Architecture: 512-256-128-256-512 Parameters: Batch Size = 128 Latent Dimensions = 128 Epochs = 128 Loss = Mean Squared Error (CNN) & KL Divergence (VAE) Activation = ReLU Learning rate = 1e-6 Optimizers: Adam Early stopping was set to patients of 10 for minimal validation loss and restoration of best weights CNN autoencoders have batch normalization layers between the dense layers. More information available at the GitHub Repo

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These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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