Geoffroy Dubourg-Felonneau | DeepAI

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∙ 12/06/2019

Deep Bayesian Recurrent Neural Networks for Somatic Variant Calling in Cancer

The emerging field of precision oncology relies on the accurate pinpoint...

47 Geoffroy Dubourg-Felonneau, et al. ∙

∙ 12/04/2019

Safety and Robustness in Decision Making: Deep Bayesian Recurrent Neural Networks for Somatic Variant Calling in Cancer

The genomic profile underlying an individual tumor can be highly informa...

0 Geoffroy Dubourg-Felonneau, et al. ∙

∙ 11/28/2019

Effective Sub-clonal Cancer Representation to Predict Tumor Evolution

The majority of cancer treatments end in failure due to Intra-Tumor Hete...

0 Adnan Akbar, et al. ∙

∙ 11/27/2019

Flatsomatic: A Method for Compression of Somatic Mutation Profiles in Cancer

In this study, we present Flatsomatic - a Variational Auto Encoder (VAE)...

0 Geoffroy Dubourg-Felonneau, et al. ∙

∙ 11/20/2019

Learning Embeddings from Cancer Mutation Sets for Classification Tasks

Analysis of somatic mutation profiles from cancer patients is essential ...

0 Geoffroy Dubourg-Felonneau, et al. ∙

∙ 11/26/2018

Interlacing Personal and Reference Genomes for Machine Learning Disease-Variant Detection

DNA sequencing to identify genetic variants is becoming increasingly val...

0 Luke R Harries, et al. ∙

∙ 11/26/2018

A Framework for Implementing Machine Learning on Omics Data

The potential benefits of applying machine learning methods to -omics da...

4 Geoffroy Dubourg-Felonneau, et al. ∙

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