Ma Q - Search Results

1

Bioinformatics tools for quantitative and functional metagenome and metatranscriptome data analysis in microbes.

Niu SY, Yang J, McDermaid A, Zhao J, Kang Y, Ma Q. Niu SY, et al. Among authors: ma q. Brief Bioinform. 2018 Mar 1;19(2):360. doi: 10.1093/bib/bby012. Brief Bioinform. 2018. PMID: 29481588 No abstract available.

2

QUBIC: a bioconductor package for qualitative biclustering analysis of gene co-expression data.

Zhang Y, Xie J, Yang J, Fennell A, Zhang C, Ma Q. Zhang Y, et al. Among authors: ma q. Bioinformatics. 2017 Feb 1;33(3):450-452. doi: 10.1093/bioinformatics/btw635. Bioinformatics. 2017. PMID: 28172469

3

An algorithmic perspective of de novo cis-regulatory motif finding based on ChIP-seq data.

Liu B, Yang J, Li Y, McDermaid A, Ma Q. Liu B, et al. Among authors: ma q. Brief Bioinform. 2018 Sep 28;19(5):1069-1081. doi: 10.1093/bib/bbx026. Brief Bioinform. 2018. PMID: 28334268 Review.

4

DMINDA 2.0: integrated and systematic views of regulatory DNA motif identification and analyses.

Yang J, Chen X, McDermaid A, Ma Q. Yang J, et al. Among authors: ma q. Bioinformatics. 2017 Aug 15;33(16):2586-2588. doi: 10.1093/bioinformatics/btx223. Bioinformatics. 2017. PMID: 28419194

5

Bioinformatics tools for quantitative and functional metagenome and metatranscriptome data analysis in microbes.

Niu SY, Yang J, McDermaid A, Zhao J, Kang Y, Ma Q. Niu SY, et al. Among authors: ma q. Brief Bioinform. 2018 Nov 27;19(6):1415-1429. doi: 10.1093/bib/bbx051. Brief Bioinform. 2018. PMID: 28481971 Review.

6

It is time to apply biclustering: a comprehensive review of biclustering applications in biological and biomedical data.

Xie J, Ma A, Fennell A, Ma Q, Zhao J. Xie J, et al. Among authors: ma a, ma q. Brief Bioinform. 2019 Jul 19;20(4):1449-1464. doi: 10.1093/bib/bby014. Brief Bioinform. 2019. PMID: 29490019 Free PMC article. Review.

7

RECTA: Regulon Identification Based on Comparative Genomics and Transcriptomics Analysis.

Chen X, Ma A, McDermaid A, Zhang H, Liu C, Cao H, Ma Q. Chen X, et al. Among authors: ma a, ma q. Genes (Basel). 2018 May 30;9(6):278. doi: 10.3390/genes9060278. Genes (Basel). 2018. PMID: 29849014 Free PMC article.

8

Interpretation of differential gene expression results of RNA-seq data: review and integration.

McDermaid A, Monier B, Zhao J, Liu B, Ma Q. McDermaid A, et al. Among authors: ma q. Brief Bioinform. 2019 Nov 27;20(6):2044-2054. doi: 10.1093/bib/bby067. Brief Bioinform. 2019. PMID: 30099484 Free PMC article. Review.

9

A New Machine Learning-Based Framework for Mapping Uncertainty Analysis in RNA-Seq Read Alignment and Gene Expression Estimation.

McDermaid A, Chen X, Zhang Y, Wang C, Gu S, Xie J, Ma Q. McDermaid A, et al. Among authors: ma q. Front Genet. 2018 Aug 14;9:313. doi: 10.3389/fgene.2018.00313. eCollection 2018. Front Genet. 2018. PMID: 30154828 Free PMC article.

10

IRIS-EDA: An integrated RNA-Seq interpretation system for gene expression data analysis.

Monier B, McDermaid A, Wang C, Zhao J, Miller A, Fennell A, Ma Q. Monier B, et al. Among authors: ma q. PLoS Comput Biol. 2019 Feb 14;15(2):e1006792. doi: 10.1371/journal.pcbi.1006792. eCollection 2019 Feb. PLoS Comput Biol. 2019. PMID: 30763315 Free PMC article.

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