A New ℓ0-Regularized Log-Linear Poisson Graphical Model with Applications to RNA Sequencing Data-Reference-Cited by-同舟云学术

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A New ℓ0-Regularized Log-Linear Poisson Graphical Model with Applications to RNA Sequencing Data

Published:2021-09-01 Issue:9 Volume:28 Page:880-891
ISSN:1557-8666
Container-title:Journal of Computational Biology
language:en
Short-container-title:Journal of Computational Biology

Author:

Li Caesar Z.¹^ORCID,Kawaguchi Eric S.²,Li Gang¹

Affiliation:

1. Department of Biostatistics, School of Public Health, University of California at Los Angeles, Los Angeles, California, USA.

2. Graduate Programs in Biostatistics and Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.

Publisher

Mary Ann Liebert Inc

Subject

Computational Theory and Mathematics,Computational Mathematics,Genetics,Molecular Biology,Modelling and Simulation

Link

https://www.liebertpub.com/doi/pdf/10.1089/cmb.2020.0558

Reference40 articles.

1. A Log-Linear Graphical Model for inferring genetic networks from high-throughput sequencing data

2. Conditional Sure Independence Screening

3. The impact of read length on quantification of differentially expressed genes and splice junction detection

4. Network analysis for count data with excess zeros

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