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Overcoming Observation Bias for Cancer Progression Modeling

; ; ; ; ; ; ; ;

In
Research in computational molecular biology : 28th Annual International Conference, RECOMB 2024, Cambridge, MA, USA, April 29-May 2, 2024 : proceedings / Jian Ma editor, Seiten/Artikel-Nr: 217-234

Konferenz/Event:28. Annual International Conference on Research in Computational Molecular Biology , Cambridge, MA , USA , RECOMB 2024 , 2024-04-29 - 2024-05-02

ImpressumCham, Switzerland : Springer

Umfang217-234

ISBN978-1-07-163990-0, 978-1-0716-3988-7, 978-1-0716-3989-4

ReiheLecture notes in computer science ; 14758

Online
DOI: 10.1007/978-1-0716-3989-4_14


Einrichtungen

  1. Lehr- und Forschungsgebiet Numerische Analysis (111620)
  2. Fachgruppe Mathematik (110000)



Dokumenttyp
Contribution to a book/Contribution to a conference proceedings

Format
online, print

Sprache
English

Anmerkung
Peer reviewed article

Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-85194257129
WOS Core Collection: WOS:001292918000014

Interne Identnummern
RWTH-2024-11073
Datensatz-ID: 997114

Beteiligte Länder
Germany, Switzerland

 GO

Related:

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Preprint  ;  ;  ;  ;  ;  ;  ;  ;
Overcoming Observation Bias for Cancer Progression Modeling
14 Seiten () [10.1101/2023.12.03.569824]  GO OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

NationallizenzNationallizenz ; SCOPUS
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Document types > Events > Contributions to a conference proceedings
Document types > Books > Contributions to a book
Faculty of Mathematics and Natural Sciences (Fac.1) > Department of Mathematics
Documents in print
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110000
111620
 Record created 2024-11-25, last modified 2025-10-06
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