Author

Theophile Langanay

New York Genome Center

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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Genomics· 2

Signature Assays, Organisms & Methods

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Organism:human· 2 Research Focus:variant calling· 2 Assay:whole-genome sequencing· 2 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Adam J. WidmaniD· 2 shared Alexandre Pellan ChengiD· 2 shared Anushri AroraiD· 2 shared Ashish SaxenaiD· 2 shared Dan Avi LandauiD· 2 shared Daniel HalmosiD· 2 shared Dennie Tompers FrederickiD· 2 shared Dina ManaaiD· 2 shared

Activity by Year

2022-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersGenomics

Adam J. WidmanORCID

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Author profile →

2 papers

Recent·Most cited

Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

Adam J. Widman, Minita J. Shah, Amanda Frydendahl, Daniel Halmos, Cole C. Khamnei, Nadia Øgaard, Srinivas Rajagopalan, Anushri Arora, Aditya S. Deshpande, William F. Hooper, Jean Quentin, Jake Bass, Mingxuan Zhang, Theophile Langanay, Laura Andersen, , Dan Avi Landau

This paper introduces MRD-EDGE, a machine learning platform for ultrasensitive ctDNA detection in plasma WGS, showing improved sensitivity and broader applicability for MRD monitoring.

Nature Medicine · Jun 1, 2024Peer-reviewedGenomics

Whole genome error-corrected sequencing for sensitive circulating tumor DNA cancer monitoring

Alexandre Pellan Cheng, Adam J. Widman, Anushri Arora, Itai Rusinek, William F. Hooper, Rebecca L. Murray, Daniel Halmos, Theophile Langanay, Giorgio Inghirami, Søren Germer, Melissa Marton, Dina Manaa, Adrienne Helland, Rob Furatero, Jaime McClintock, , Dan Avi Landau

This study applies low-cost whole genome sequencing to detect circulating tumor DNA at high sensitivity in plasma samples, achieving error rates as low as 10^-7 and enabling cancer monitoring without matched tumor sequencing.

bioRxiv · Nov 17, 2022 · PreprintGenomics