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NrGe-DTL: a computational framework for cancer drug respons..:
, In:
2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
,
Zhang, Yuchen
;
Lian, Linghang
;
Yang, Xuhua
- p. 440-445 , 2023
Link:
https://doi.org/10.1109/BIBM58861.2023.10385310
RT T1 <cTitle>2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)</cTitle>: T1 <Title>NrGe-DTL: a computational framework for cancer drug response prediction based on deep transfer learning from combined denoised genomic profiles and chemical structure embedding of drugs</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10385310&Exemplar=1&LAN=DE A1 Zhang, Yuchen A1 Lian, Linghang A1 Yang, Xuhua YR 2023 SN 2156-1133 K1 Precision medicine K1 Computational modeling K1 Transfer learning K1 Genomics K1 Predictive models K1 Cancer drugs K1 Feature extraction K1 precision medicine K1 drug response K1 chemical structure information K1 denoising autoencoder K1 transfer learning SP 440 OP 445 LK http://dx.doi.org/https://doi.org/10.1109/BIBM58861.2023.10385310 DO https://doi.org/10.1109/BIBM58861.2023.10385310 SF ELIB - SuUB Bremen
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