PuSH - Publication Server of Helmholtz Zentrum München

An, U.* ; Cai, N. ; Dahl, A.* ; Sankararaman, S.*

AutoComplete: Deep learning-based phenotype imputation for large-scale biomedical data.

Lect. Notes Comput. Sc. 13278 LNBI, 385-386 (2022)
DOI
Open Access Green as soon as Postprint is submitted to ZB.
Biomedical datasets that aim to collect diverse phenotypic and genomic data across large numbers of individuals are plagued by the large fraction of missing data The ability to accurately impute or “fill-in” missing entries in these datasets is critical to a number of downstream applications.
Altmetric
Additional Metrics?
[➜Log in]
Edit extra informations Login
Publication type Article: Journal article
Document type Meeting abstract
Corresponding Author
ISSN (print) / ISBN 0302-9743
e-ISSN 1611-3349
Conference Title 26th International Conference on Research in Computational Molecular Biology, RECOMB 2022
Conference Date 22-25 May 2022
Conference Location San Diego, California, United States
Journal Lecture Notes in Computer Science
Quellenangaben Volume: 13278 LNBI, Issue: , Pages: 385-386 Article Number: , Supplement: ,
Publisher Springer
Publishing Place Berlin [u.a.]
Non-patent literature Publications
Institute(s) Helmholtz Pioneer Campus (HPC)