More for less: predicting and maximizing genomic variant discovery via Bayesian nonparametrics
<jats:title>Summary</jats:title> <jats:p>While the cost of sequencing genomes has decreased dramatically in recent years, this expense often remains nontrivial. Under a fixed budget, scientists face a natural trade-off between quantity and quality: spending resource...
Main Authors: | Masoero, Lorenzo, Camerlenghi, Federico, Favaro, Stefano, Broderick, Tamara |
---|---|
Other Authors: | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
Format: | Article |
Language: | English |
Published: |
Oxford University Press (OUP)
2022
|
Online Access: | https://hdl.handle.net/1721.1/142893 |
Similar Items
-
Improved prediction and optimal sequencing strategies for genomic variant discovery via Bayesian nonparametrics
by: Masoero, Lorenzo
Published: (2022) -
Genomic variety estimation with Bayesian nonparametric hierarchies
by: Masoero, Lorenzo.
Published: (2019) -
Truncated Bayesian nonparametrics
by: Campbell, Trevor D. J. (Trevor David Jan)
Published: (2017) -
Nonparametric Bayesian behavior modeling
by: Joseph, Joshua Mason
Published: (2009) -
More with less
by: Lim, Amanda Jane Yi Kuan, et al.
Published: (2020)