Article

Aggregation Tool for Genomic Concepts (ATGC): A deep learning framework for somatic mutations and other sparse genomic measures

2020-08-07

Abstract excerpt

<h4>ABSTRACT</h4> Deep learning can extract meaningful features from data given enough training examples. Large-scale genomic data are well suited for this class of machine learning algorithms; however, for many of these data the labels are at the level of the sample instead of at the level of the individual genomic measures. Conventional approaches to this data statically featurise and aggregate the measures sep...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 289a2be8-3c26-5fbd-a561-ec34843917ff
DOI: 10.1101/2020.08.05.237206

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Aggregation Tool for Genomic Concepts (ATGC): A deep learning framework for somatic mutations and other sparse genomic measuresDOI 10.1101/2020.08.05.237206Read

Multiple-instance learning of somatic mutations for the classification of tumour type and the prediction of microsatellite status.Semantic proximity Read

Semantic fragment representations for coordinate-free analysis of genomics dataSemantic proximity Read

Mutation-Attention (MuAt): deep representation learning of somatic mutations for tumour typing and subtypingSemantic proximity Read

CNAttention: an attention-based deep multiple-instance method for uncovering CNA signatures across cancersSemantic proximity Read

Mutation-Attention (MuAt): deep representation learning of somatic mutations for tumour typing and subtyping.Semantic proximity Read

Pan-cancer tumour classification and risk stratification from whole-genome somatic variants via dual-task representation learningSemantic proximity Read

PICASA: Decomposing patient heterogeneity of single-cell cancer data by cross-attention neural networksSemantic proximity Read

Incorporating Hierarchical Information into Multiple Instance Learning for Patient Phenotype Prediction with scRNA-seq DataSemantic proximity Read

Learning Patient Similarity from Genomics for Precision OncologySemantic proximity Read

An Enhanced Variant-Aware Deep Learning Model for Individual Gene Expression PredictionSemantic proximity Read

End-to-end deep learning versus machine learning for biomarker discovery in cancer genomesSemantic proximity Read

Benchmarking DNA Foundation Models for Genomic and Genetic TasksSemantic proximity Read