Rfcaller: a machine Learning approach combined with read-level features to detect somatic mutations
Publication date:
Publisher version:
Citación:
ISSN:
Patrocinado por:
Ministerio de Ciencia e Innovaci on [SAF2017-87811-R, PID2020-117185RB-I00]; Fundación científica Asociacion española Contra el Cancer (AECC); Centro de investigación Biomedica en Red de Cancer (CIBERONC); Instituto de Salud Carlos III; European Union (ERDF/ESF, Investing in your future') [PMP15/00007, PI17/01061]; La Caixa' Foundation CLLEvolution [HR17-00221]; Ministerio de Economía y Competitividad (MINECO) [RTI2018-094274-B-I00]; Generalitat de Catalunya AGAUR [2021-SGR-01293, 2017-SGR-1142]; Department of Education of the Basque Government [PRE 2017 1 0100]; Asturian Government; 2021 AACR-Amgen Fellowship in Clinical/Translational Cancer Research [21-40-11-NADE]; European Hematology Association (EHA) Junior Research Gran [RG-202012-00245]; Lady Tata Memorial Trust [LADY TATA 21 3223]
Collections
- Artículos [36123]
- Bioquímica y Biología Molecular [266]