In silico resources for (canine) la genomics/transcriptomics.

We develop and use bioinformatics tools for genomics and transcriptomics projects related to fundamental research questions such as:

  • deep-learning approaches to predict gene expression and thus the impact of regulatory mutations on gene expression.
  • genome annotation and more specifically the identification of long non-coding RNAs (lncRNAs) from short and long transcriptomic data (SR- and LR-RNAseq).
  • comparative genomics, the study of directional selection and evolution in canines

We provide bioinformatics programs and web servers such as :


References :

[1] Kergal et al, Gene Expression in dogs prediction using Deep Learning (2022). https://github.com/ckergal/BLIMP

[2] Wucher, V. et al. FEELnc: a tool for long non-coding RNA annotation and its application to the dog transcriptome. Nucleic Acids Res gkw1306 (2017). doi:10.1093/nar/gkw1306

[3] Derrien, T., André, C., Galibert, F. & Hitte, C. AutoGRAPH: an interactive web server for automating and visualizing comparative genome maps. Bioinformatics 23, 498-499 (2007).

[4] Berglund, J. et al. Novel origins of copy number variation in the dog genome. Genome Biol 13, R73 (2012).

[5] Vaysse, A. et al. Identification of genomic regions associated with phenotypic variation between dog breeds using selection mapping. PLoS Genet 7, e1002316 (2011).