A dual-level sparsity Bayesian framework for rare-variant association analysis using integrated nested laplace approximation.

Li C, Mei B

DOI: 10.1142/s0219720026500125
Published: 2026 Oct 8
Container: Journal of bioinformatics and computational biology
Publisher: Not recorded
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1142/s0219720026500125,
  title = {A dual-level sparsity Bayesian framework for rare-variant association analysis using integrated nested laplace approximation.},
  author = {Li C and Mei B},
  year = {2026},
  journal = {Journal of bioinformatics and computational biology},
  doi = {10.1142/s0219720026500125},
  url = {https://doi.org/10.1142/s0219720026500125}
}

RIS

TY  - JOUR
TI  - A dual-level sparsity Bayesian framework for rare-variant association analysis using integrated nested laplace approximation.
AU  - Li C
AU  - Mei B
PY  - 2026
JO  - Journal of bioinformatics and computational biology
DO  - 10.1142/s0219720026500125
UR  - https://doi.org/10.1142/s0219720026500125
ER  -

APA

C, L., & B, M. (2026). A dual-level sparsity Bayesian framework for rare-variant association analysis using integrated nested laplace approximation.. Journal of bioinformatics and computational biology. https://doi.org/10.1142/s0219720026500125

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pubmed · retrieved 2026-11-10T13:32:39.125Z