Inferring cancer progression from Single-Cell Sequencing while allowing mutation losses is a research paper published in Bioinformatics (2020). On theSindex it has a DataRank of 0. It has been cited 52 times.
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Marie Skłodowska-Curie
Grant: 872539
Pan-genome Graph Algorithms and Data Integration
NIH
Grant: 1T32GM083937
US National Science Foundation
Grant: IIS-1840275
NIGMS NIH HHS
Grant: T32 GM083937
National Institutes of Health
Grant: 5T32GM083937-05
Tri-Institutional Training Program in Computational Biology & Medicine
National Science Foundation
Grant: 1840275
EAGER: Novel Computational Models and Algorithms for Mapping Link-Read Sequencing Data
European Union’s Horizon 2020 research and innovation programme
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals
Additional file 1 of The Bourque distances for mutation trees of cancers
Additional file 1 of The Bourque distances for mutation trees of cancers
Additional file 2 of The Bourque distances for mutation trees of cancers
Additional file 2 of The Bourque distances for mutation trees of cancers
Additional file 3 of The Bourque distances for mutation trees of cancers
Additional file 3 of The Bourque distances for mutation trees of cancers
Additional file 1 of ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model
Additional file 1 of ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model
Additional file 2 of ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model
Additional file 2 of ConDoR: tumor phylogeny inference with a copy-number constrained mutation loss model