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Peer-reviewed Journal Articles

* Co-first author

Li B, Li Y, Qin Z. (2016) Improving hierarchical models using historical data with applications in high throughput genomics data analysis. Statistics in Biosciences. 1-18.

Qin Z, Li B, Conneely KN, Wu H, Hu M, Ayyala D, Park Y, Jin VX, Zhang F, Zhang H, Li L, Lin S. (2016) Statistical challenges in analyzing methylation and long-range chromosomal interaction data. Statistics in Biosciences. 1-26.

Joseph SJ, Li B, Petit RA, Qin Z, Darrow L, Read TD. (2016) The single-species metagenome: subtyping Staphylococcus aureus core genome sequences from shotgun metagenomic data. PeerJ. 4:e2571.

Li B, Sun Z, He Q, Zhu Y, Qin ZS. (2015) Bayesian inference with historical data-based informative priors improves detection of differentially expressed genes. Bioinformatics. 32(5):682-689.

Wu H, Xu T, Feng H, Chen L, Li B, Yao B, Qin Z, Jin P, Conneely KN. (2015) Detection of differentially methylated regions from whole-genome bisulfite sequencing data without replicates. Nucleic Acids Research. 43(21):e141.

Xu T*, Li B*, Zhao M, Szulwach KE, Street RC, Lin L, Yao B, Zhang F, Jin P, Wu H, Qin ZS. (2015) Base-resolution methylation patterns accurately predict transcription factor bindings in vivo. Nucleic Acids Research. 43(5):2757-66.

Joseph SJ, Li B, Ghonasgi T, Haase CP, Qin ZS, Dean D, Read TD. (2014) Direct amplification, sequencing and profiling of Chlamydia trachomatis strains in single and mixed infection clinical samples. PLoS ONE. 9(6).

Aly SS, Zhao J, Li B, Jiang J. (2014) Reliability of environmental sampling culture results using the negative binomial intraclass correlation coefficient. Springerplus. 3:40.

Working Papers

Li B, Qin ZS, Wu H. A novel statistical method for differential expression analysis of single cell RNA-Seq data.

Li B, Qin ZS. IPBTSeq: Using historical data to improve the analysis of RNA-Seq Data.

Li B, Qin ZS. Comparative analyses of whole-genome bisulfite sequencing data across multiple cell types and species.

Li B, Dileep V, Gilbert DM, Qin ZS. RepliHMM: A Hidden Markov Model based method on the discovery of replication timing states.