Author

Tristan Meynier Georges

ETH Zurich

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:contrastive learning· 1 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1 Research Focus:gene regulatory network inference· 1 Assay:Hi-C· 1 Research Focus:variant calling· 1

Frequent Co-Authors

Marianna RapsomanikiiD· 1 shared

Activity by Year

2021-2021 · peak 1/yr

1 paper

Recent·Most cited

BioinformaticsbioRxivPreprintDec 15, 2021

Modeling the Three-Dimensional Chromatin Structure from Hi-C Data with Transfer Learning

Tristan Meynier Georges, Marianna Rapsomaniki

This paper introduces TECH-3D, a transfer learning method for 3D chromatin structure prediction from Hi-C data, outperforming previous methods without assuming contact frequency equals Euclidean distance.

2 citations

Hi-Cdeep learning

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