Prediction of single-cell miRNA-seq data in cancer


microRNAs (miRNAs) are small non-coding RNAs known to further regulate protein coding genes. They are important in many physiological and pathological processes. In cancer, in particular, they were demonstrated to be implicated to all the carcinogenesis: initiation, propagation and metastasis.
Single cell mRNA-seq has revolutionized are vision of tumor composition, further decrypting the cross-talk between tumor cells and cells of the microenvironment. Many public datasets exist for various cancer subtypes. Single cell miRNA sequencing has recently been proven, but is difficult and public datasets are rare (and will remain rare for a long time).


The goal of the internship is first to predict single cell miRNA-seq data from public single cell mRNA-seq datasets in cancer. Then, the method will be evaluated with experimental single cell miRNA-seq data.
A particular focus will be given to carcinomas of kidney and surrenal gland, which are well studied in the hosting team.
The research will be conducted in a small and dynamic team composed of both bioinformaticians and wet lab biologists.

Supervisor: Laurent Guyon; (contact email)

Funding & duration: The intern student receives a “gratification”. 4-6 months

Web links:

Keywords: data analysis, bioinformatics, systems biology, miRNAs, single cell mRNA-seq

Requirements: (ongoing) master2 studies in bioinformatics or applied math, with strong interest in biology and cancer. Excellent ranking, top 20% (send marks and rank, even if unofficial at this stage). Ideally, wish to pursue through PhD studies.

Related publications of the team:

  1. Giroux, P., Bhajun, R., Segard, S., Picquenot, C., Charavay, C., Desquilles, L., … & Guyon, L. (2020). miRViz: a novel webserver application to visualize and interpret microRNA datasets. Nucleic Acids Research.

  2. Cherradi N. microRNAs as Potential Biomarkers in Adrenocortical Cancer: Progress and Challenges. Front Endocrinol (Lausanne). 2016;6:195.

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