| Property | Value |
|---|
| Working Groups |  Hemmer, Müller-Myhsok, Theis |
| Subproject | None |
| Open Access |  Yes |
| Publication Type | Journal Article |
| Peer Reviewed | Yes |
| PMID |  32012148 |
| DOI |  10.1371/journal.pcbi.1007616 |
| Publication Year | 2020 |
| Title | DeepWAS: Multivariate genotype-phenotype associations by directly integrating regulatory information using deep learning.  |
| Journal | PLoS computational biology |
| ISSN | 1553-734X |
| ESSN | 1553-7358 |
| URL | https://www.ncbi.nlm.nih.gov/pubmed/?term=32012148%5Buid%5D |
| Pages | e1007616 |
| Issue | 2 |
| Volume | 16 |
| Journal Abbreviation | PLoS Comput Biol |
| Authors | Arloth J, Eraslan G, Andlauer TFM, Martins J, Iurato S, Kühnel B, Waldenberger M, Frank J, Gold R, Hemmer B, Luessi F, Nischwitz S, Paul F, Wiendl H, Gieger C, Heilmann-Heimbach S, Kacprowski T, Laudes M, Meitinger T, Peters A, Rawal R, Strauch K, Lucae S, Müller-Myhsok B, Rietschel M, Theis FJ, Binder EB, Mueller NS |
| First Author | Arloth J |
| Last Author | Mueller NS |
| Scholia |  Wikidata-based representation at Scholia |
External Resources
Q89505417https://www.wikidata.org/wiki/Q89505417
Wikidata ID
