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Orthanq: transparent and uncertainty-aware haplotype quantification with application in HLA-typing

• Authors : Hamdiye Uzuner; Annette Paschen; Dirk Schadendorf

Subjects: Haplotype quantification; HLA typing; Bayesian latent variable model

• Source: BMC Bioinformatics, Vol 25, Iss 1, Pp 1-18 (2024)

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A phenome-guided drug repositioning through a latent variable model.

• Authors : Bisgin, Halil¹ (AUTHOR); Zhichao Liu¹ (AUTHOR); Hong Fang² (AUTHOR)

• Source: BMC Bioinformatics. 2014, Vol. 15 Issue 1, p1-12. 12p. 2 Diagrams, 2 Charts, 2 Graphs.

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Orthanq: transparent and uncertainty-aware haplotype quantification with application in HLA-typing.

• Authors : Uzuner, Hamdiye¹ (AUTHOR) ; Paschen, Annette^2,3 (AUTHOR); Schadendorf, Dirk^2,3 (AUTHOR)

• Source: BMC Bioinformatics. 7/16/2024, Vol. 25 Issue 1, p1-18. 18p.

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A robust nonlinear low-dimensional manifold for single cell RNA-seq data

• Authors : Archit Verma; Barbara E. Engelhardt

Subjects: Manifold learning; Single cell RNA sequencing; Gaussian process latent variable model

• Source: BMC Bioinformatics, Vol 21, Iss 1, Pp 1-15 (2020)

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A robust nonlinear low-dimensional manifold for single cell RNA-seq data.

• Authors : Verma, Archit¹ (AUTHOR); Engelhardt, Barbara E.² (AUTHOR)

• Source: BMC Bioinformatics. 7/21/2020, Vol. 21 Issue 1, p1-15. 15p. 7 Graphs.

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Improving RNA-Seq expression estimation by modeling isoform- and exon-specific read sequencing rate

• Authors : Chunlin Chen; Li Zhang; Xuejun Liu

Subjects: Gene isoform; RNA-Seq; Latent variable

• Source: BMC Bioinformatics

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Improving RNA-Seq expression estimation by modeling isoform- and exon-specific read sequencing rate.

• Authors : Xuejun Liu¹ ; Xinxin Shi¹; Chunlin Chen¹

• Source: BMC Bioinformatics. 10/16/2015, Vol. 16, p1-13. 13p. 2 Diagrams, 5 Charts, 6 Graphs.

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Identifying novel associations in GWAS by hierarchical Bayesian latent variable detection of differentially misclassified phenotypes.

• Authors : Shafquat, Afrah¹ (AUTHOR); Crystal, Ronald G.^2,3 (AUTHOR); Mezey, Jason G.^1,2 (AUTHOR)

• Source: BMC Bioinformatics. 5/7/2020, Vol. 21 Issue 1, p1-25. 25p. 3 Diagrams, 4 Charts, 5 Graphs.

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Identifying novel associations in GWAS by hierarchical Bayesian latent variable detection of differentially misclassified phenotypes

• Authors : Afrah Shafquat; Ronald G. Crystal; Jason G. Mezey

Subjects: GWAS; Misclassification; Bayesian

• Source: BMC Bioinformatics, Vol 21, Iss 1, Pp 1-25 (2020)

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Semi-supervised discovery of differential genes

• Authors : Oba Shigeyuki; lshii Shin

Subjects: Computer applications to medicine. Medical informatics; R858-859.7; Biology (General)

• Source: BMC Bioinformatics, Vol 7, Iss 1, p 414 (2006)

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