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  • R. El Helou, G. Pinna, O. Cabaud, J. Wicinski, R. Bhajun, L. Guyon, C. Rioualen, P. Finetti, A. Gros, B. Mari, P. Barbry, F. Bertucci, G. Bidaut, A. Harel-Bellan, D. Birnbaum, E. Charafe-Jauffret, et C. Ginestier, « miR-600 Acts as a Bimodal Switch that Regulates Breast Cancer Stem Cell Fate through WNT Signaling », Cell Reports, vol. 18, nᵒ 9, p. 2256-2268, 2017.

  • S. Robinson, J. Nevalainen, G. Pinna, A. Campalans, J. P. Radicella, et L. Guyon, « Incorporating interaction networks into the determination of functionally related hit genes in genomic experiments with Markov random fields », Bioinformatics (Oxford, England), vol. 33, nᵒ 14, p. i170-i179, juill. 2017.
    Résumé : Motivation: Incorporating gene interaction data into the identification of 'hit' genes in genomic experiments is a well-established approach leveraging the 'guilt by association' assumption to obtain a network based hit list of functionally related genes. We aim to develop a method to allow for multivariate gene scores and multiple hit labels in order to extend the analysis of genomic screening data within such an approach. Results: We propose a Markov random field-based method to achieve our aim and show that the particular advantages of our method compared with those currently used lead to new insights in previously analysed data as well as for our own motivating data. Our method additionally achieves the best performance in an independent simulation experiment. The real data applications we consider comprise of a survival analysis and differential expression experiment and a cell-based RNA interference functional screen. Availability and implementation: We provide all of the data and code related to the results in the paper. Contact: or Supplementary information: Supplementary data are available at Bioinformatics online.
    Mots-clés : PARI, PF.


  • E. Deforzh, T. Vargas, J. Kropp, M. Vandamme, G. Pinna, et A. Polesskaya, « IMP-3 protects the mRNAs of cyclins D1 and D3 from GW182/AGO2-dependent translational repression », International Journal of Oncology, oct. 2016.
    Mots-clés : DBG, PARI, PF, RPTEG.

  • A. Polesskaya, G. Pinna, Y. Sassi, M. Vandamme, A. Bigot, V. Mouly, N. Morozova, A. Harel-Bellan, et C. Degerny, « Post-transcriptional modulation of interleukin 8 by CNOT6L regulates skeletal muscle differentiation », Biochimica Et Biophysica Acta (BBA) -Molecular Cell Research, vol. 1863, nᵒ 2, p. 263-270, févr. 2016.
    Résumé : CNOT6L is a deadenylase subunit belonging to the CCR4-NOT complex, a major deadenylase complex in eukaryotes involved at multiple levels in regulation of gene expression. While CNOT6L is expressed in skeletal muscle cells, its specific functions in this tissue are still largely unknown. Our previous work highlighted the functional of CNOT6L in skeletal muscle cell differentiation. To further explore how CNOT6L regulates myogenesis, we used here gene expression analysis to identify CNOT6L mRNA targets in human myoblasts. Among these novel targets, IL-8 (interleukin 8) mRNA was the most upregulated in CNOT6L knock-down (KD) cells. Biochemical approaches and poly (A) tail length assays showed that IL-8 mRNA is a direct target of CNOT6L, and further investigations by loss- and gain-of-function assays pointed out that IL-8 is an important effector of myogenesis. Therefore, we have characterized CNOT6L-IL-8 as a new signaling axis that regulates myogenesis.
    Mots-clés : Adult, Animals, Blotting, Western, Cell Differentiation, Cell Line, Cells, Cultured, CNOT6L, DBG, Differentiation, Gene Expression Profiling, Humans, IL-8, Interleukin-8, Microscopy, Fluorescence, Muscle Development, Muscle Fibers, Skeletal, Muscle, Skeletal, Myoblasts, Myogenesis, Oligonucleotide Array Sequence Analysis, PARI, PF, Post-transcriptional regulation, Reverse Transcriptase Polymerase Chain Reaction, Ribonucleases, RNA Interference, RNA, Messenger, RPTEG, Signal Transduction, Transcription, Genetic.


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