Cargando…
Tumor Phylogeny Topology Inference via Deep Learning
Principled computational approaches for tumor phylogeny reconstruction via single-cell sequencing typically aim to build the most likely perfect phylogeny tree from the noisy genotype matrix – which represents genotype calls of single cells. This problem is NP-hard, and as a result, existing approac...
Autores principales: | Sadeqi Azer, Erfan, Haghir Ebrahimabadi, Mohammad, Malikić, Salem, Khardon, Roni, Sahinalp, S. Cenk |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7582044/ https://www.ncbi.nlm.nih.gov/pubmed/33117968 http://dx.doi.org/10.1016/j.isci.2020.101655 |
Ejemplares similares
-
Integrative inference of subclonal tumour evolution from single-cell and bulk sequencing data
por: Malikic, Salem, et al.
Publicado: (2019) -
A multi-labeled tree dissimilarity measure for comparing “clonal trees” of tumor progression
por: Karpov, Nikolai, et al.
Publicado: (2019) -
PhISCS: a combinatorial approach for subperfect tumor phylogeny reconstruction via integrative use of single-cell and bulk sequencing data
por: Malikic, Salem, et al.
Publicado: (2019) -
Volatile compounds analysis and antioxidant, antimicrobial and cytotoxic activities of Mindium laevigatum
por: Ebrahimabadi, Abdolrasoul Haghir, et al.
Publicado: (2016) -
Cypiripi: exact genotyping of CYP2D6 using high-throughput sequencing data
por: Numanagić, Ibrahim, et al.
Publicado: (2015)