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DAGBagM: learning directed acyclic graphs of mixed variables with an application to identify protein biomarkers for treatment response in ovarian cancer

• Authors : Chowdhury, Shrabanti; Wang, Ru; Yu, Qing

Subjects: Information and Computing Sciences; Machine Learning; Rare Diseases

• Source: BMC Bioinformatics. 23(1)

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Mind the gaps: overlooking inaccessible regions confounds statistical testing in genome analysis.

• Authors : Domanska D; Department of Informatics, University of Oslo, Oslo, Norway. .; Kanduri C

Subjects: Confounding Factors, Epidemiologic* ; Genome, Human* ; High-Throughput Nucleotide Sequencing*

• Source: BMC bioinformatics [BMC Bioinformatics] 2018 Dec 14; Vol. 19 (1), pp. 481. Date of Electronic Publication: 2018 Dec Publisher: BioMed Central Country of Publication: England NLM ID: 100965194 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2105

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Feature selection and causal analysis for microbiome studies in the presence of confounding using standardization.

• Authors : Goren, Emily; Wang, Chong; He, Zhulin

Subjects: Animals; Humans; Plants

• Source: BMC bioinformatics. 22(1)

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A model-based clustering via mixture of hierarchical models with covariate adjustment for detecting differentially expressed genes from paired design.

• Authors : Zhang, Yixin¹ (AUTHOR); Liu, Wei² (AUTHOR) ; Qiu, Weiliang³ (AUTHOR)

• Source: BMC Bioinformatics. 11/8/2023, Vol. 24 Issue 1, p1-18. 18p.

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DAGBagM: learning directed acyclic graphs of mixed variables with an application to identify protein biomarkers for treatment response in ovarian cancer

• Authors : Shrabanti Chowdhury; Ru Wang; Qing Yu

Subjects: Proteomics; Bioinformatics; Hill climbing

• Source: BMC bioinformatics, vol 23, iss 1

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Examining the role of unmeasured confounding in mediation analysis with genetic and genomic applications.

• Authors : Lutz SM; Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, 13001 E. 17th Place, B119 Bldg. 500 W3128, Aurora, CO, 80045, USA. .; Thwing A

Subjects: Pulmonary Disease, Chronic Obstructive/Pulmonary Disease, Chronic Obstructive/Pulmonary Disease, Chronic Obstructive/*epidemiology; Confounding Factors, Epidemiologic ; Genome-Wide Association Study

• Source: BMC bioinformatics [BMC Bioinformatics] 2017 Jul 19; Vol. 18 (1), pp. 344. Date of Electronic Publication: 2017 Jul Publisher: BioMed Central Country of Publication: England NLM ID: 100965194 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2105

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MR-GGI: accurate inference of gene–gene interactions using Mendelian randomization.

• Authors : Oh, Wonseok¹ (AUTHOR); Jung, Junghyun² (AUTHOR); Joo, Jong Wha J.^3,4 (AUTHOR)

• Source: BMC Bioinformatics. 5/15/2024, Vol. 25 Issue 1, p1-16. 16p.

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Detecting disease-associated genes with confounding variable adjustment and the impact on genomic meta-analysis: with application to major depressive disorder.

• Authors : Wang X; Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA 15261, USA.; Lin Y

Subjects: Depressive Disorder, Major/Depressive Disorder, Major/Depressive Disorder, Major/*genetics; Biomarkers ; Case-Control Studies

• Source: BMC bioinformatics [BMC Bioinformatics] 2012 Mar 29; Vol. 13, pp. 52. Date of Electronic Publication: 2012 Mar 29.Publisher: BioMed Central Country of Publication: England NLM ID: 100965194 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2105

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Examining the role of unmeasured confounding in mediation analysis with genetic and genomic applications

• Authors : Christopher D. Baker; Sharon M. Lutz; Debashis Ghosh

Subjects: 0301 basic medicine; Mediation (statistics); Confounding Factors (Epidemiology)

• Source: BMC BioinformaticsBMC Bioinformatics, Vol 18, Iss 1, Pp 1-6 (2017)

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A model-based clustering via mixture of hierarchical models with covariate adjustment for detecting differentially expressed genes from paired design

• Authors : Yixin Zhang; Wei Liu; Weiliang Qiu

Subjects: Curse of dimensionality; Confounding; EM algorithm

• Source: BMC Bioinformatics, Vol 24, Iss 1, Pp 1-18 (2023)

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