Author

Congzheng Song

Cornell UniversityORCID 0000-0002-5076-7299Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Assay:whole-exome sequencing· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Chengliang Dong· 1 shared Daniel Jay BratiD· 1 shared David A. GutmaniD· 1 shared Fatemeh AmrollahiiD· 1 shared Jose Enrique Velazquez Vega· 1 shared Joshua E. LewisiD· 1 shared Lee CooperiD· 1 shared Mohamed T. AmgadiD· 1 shared

Activity by Year

2017-2017 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Chengliang Dong

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1 paper

Recent·Most cited

Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models

Safoora Yousefi, Fatemeh Amrollahi, Mohamed T. Amgad, Chengliang Dong, Joshua E. Lewis, Congzheng Song, David A. Gutman, Sameer H. Halani, Jose Enrique Velazquez Vega, Daniel Jay Brat, Lee Cooper

This paper applies deep learning and Bayesian optimization to predict cancer clinical outcomes from genomic data, showing improved prognostic accuracy through transfer learning and providing an open-source framework.

Scientific Reports · Sep 11, 2017Peer-reviewedBioinformatics