Effective Clustering for Single Cell Sequencing Cancer Data

Effective Clustering for Single Cell Sequencing Cancer Data

Single cell sequencing (SCS) technologies provide a level of resolution that makes it indispensable for inferring from a sequenced tumor, evolutionary trees or phylogenies representing an accumulation of cancerous mutations. A drawback of SCS is elevated false negative and missing value rates, resul...

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Bibliographic Details
Main Authors: Bonizzoni, P. (Author), Ciccolella, S. (Author), Della Vedova, G. (Author), Patterson, M. (Author)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2021
Subjects:
algorithm
Algorithms
article
bioinformatics
cancer growth
Cancer progression
Cells
cluster analysis
Cluster Analysis
clustering
Clustering procedure
Cytology
Evolutionary tree
False negatives
genetics
High-precision
HTTP
human
Humans
Inference methods
Large spaces
licence
Matrix algebra
Missing values
mutation
Mutation
neoplasm
Neoplasms
phylogeny
Phylogeny
pipeline
sequential analysis
single cell sequencing
Single cells
software
Software
system analysis
Thermoplastics
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