Academic Bibliography

 Search 200 years of publications by Ghent University researchers.
Advanced search
1 file | 18.80 MB
Add to list
  1. Search results
  2. Addressing challenges in transcriptom...

Addressing challenges in transcriptome annotation and cell-type heterogeneity through integration of omics datasets and computational deconvolution

Francisco Avila Cobos (UGent)
(2020)
Author
Promoter
(UGent) and (UGent)
Organization

Downloads

  • Download
    biblio PhD thesis Francisco AvilaCobos.pdf
    • full text (Published version)
    • |
    • open access
    • |
    • PDF
    • |
    • 18.80 MB

Citation

Please use this url to cite or link to this publication:

MLA
Avila Cobos, Francisco. Addressing Challenges in Transcriptome Annotation and Cell-Type Heterogeneity through Integration of Omics Datasets and Computational Deconvolution. Universiteit Gent. Faculteit Geneeskunde en Gezondheidswetenschappen, 2020.
APA
Avila Cobos, F. (2020). Addressing challenges in transcriptome annotation and cell-type heterogeneity through integration of omics datasets and computational deconvolution. Universiteit Gent. Faculteit Geneeskunde en Gezondheidswetenschappen.
Chicago author-date
Avila Cobos, Francisco. 2020. “Addressing Challenges in Transcriptome Annotation and Cell-Type Heterogeneity through Integration of Omics Datasets and Computational Deconvolution.” Universiteit Gent. Faculteit Geneeskunde en Gezondheidswetenschappen.
Chicago author-date (all authors)
Avila Cobos, Francisco. 2020. “Addressing Challenges in Transcriptome Annotation and Cell-Type Heterogeneity through Integration of Omics Datasets and Computational Deconvolution.” Universiteit Gent. Faculteit Geneeskunde en Gezondheidswetenschappen.
Vancouver
1.
Avila Cobos F. Addressing challenges in transcriptome annotation and cell-type heterogeneity through integration of omics datasets and computational deconvolution. Universiteit Gent. Faculteit Geneeskunde en Gezondheidswetenschappen; 2020.
IEEE
[1]
F. Avila Cobos, “Addressing challenges in transcriptome annotation and cell-type heterogeneity through integration of omics datasets and computational deconvolution,” Universiteit Gent. Faculteit Geneeskunde en Gezondheidswetenschappen, 2020.
@phdthesis{8664638,
  author       = {{Avila Cobos, Francisco}},
  language     = {{eng}},
  pages        = {{178}},
  publisher    = {{Universiteit Gent. Faculteit Geneeskunde en Gezondheidswetenschappen}},
  school       = {{Ghent University}},
  title        = {{Addressing challenges in transcriptome annotation and cell-type heterogeneity through integration of omics datasets and computational deconvolution}},
  year         = {{2020}},
}