denoising



SABILab is a consulting company that aims at supporting scientific research by providing data/bio-image analysis expertise to scientists. It also has an academic research activity.

How Can We Help?

Can we assist you in your data analysis needs?

We offer a variety of services to help you improve your data production pipeline (data acquisition, image processing, statistical processing), including diagnostic evaluations, design and implementation of data analysis pipelines using open-source software, and tailored image processing methods. We also provide training in image analysis, deep learning, and statistical processing with R and Python. Check out our research works page for examples of our capabilities and let us know how we can assist you.

Jean Ollion

Founder of SABILab

ID As a trained scientist with a double expertise in cell biology and bio-image analysis, I have extensive experience in both experimental work and data analysis. During my PhD and post-doctoral studies, I developed two software tools: TANGO for 3D analysis of nuclear organization and BACMMAN for high-throughput analysis of Mother Machine
The Mother machine is a popular microfluidic device that allows long-term time-lapse imaging of thousands of cells in parallel by microscopy. It has become a valuable tool for single-cell level quantitative analysis and characterization of many cellular processes such as gene expression and regulation, mutagenesis or response to antibiotics. data.

I now work as a data scientist and bio-image analyst, providing expertise to other scientists. My background in biology allows me to understand the scientific and technical aspects of data analysis. I also continue to conduct research, recently developing an original bio-image processing method involving deep learning. I am currently working on a general purpose denoising method based on deep neural networks.

Education & Experience

  • 2016 - 2017: Université Paris Saclay: Deep Learning course from Data Science Master’s degree (external candidate)
  • 2015 - 2019: Laboratoire Jean Perrin CNRS / Sorbonne Université : Post-doctoral fellow: Mutation dynamics in single bacteria cells. Experience in microfluidics, microscopy, image processing and analysis
  • 2010 - 2014: Dynamique et régulation des génomes, National Museum of Natural History: PhD Nuclear organization of centromeric DNA in human cells. Experience in cell biology, microscopy, image processing and analysis
  • 2009 - 2010: Sorbonne Université: Master’s degree Molecular and cellular biology
  • 2006 - 2010: Ecole polytechnique alumni. General scientific training - specialization in biology.

Publications

  1. J. Ollion, C. Ollion, E. Gassiat, L. Lehéricy, and S. L. Corff, “Joint self-supervised blind denoising and noise estimation,” arXiv preprint arXiv:2102.08023, 2021.
    https://arxiv.org/abs/2102.08023
  2. J. Ollion and C. Ollion, “DistNet: Deep Tracking by displacement regression: application to bacteria growing in the Mother Machine,” 2020.
  3. L. Robert, J. Ollion, and M. Elez, “Real-time visualization of mutations and their fitness effects in single bacteria,” Nature protocols, vol. 14, no. 11, pp. 3126–3143, 2019.
  4. J. Ollion, M. Elez, and L. Robert, “High-throughput detection and tracking of cells and intracellular spots in mother machine experiments,” Nature protocols, vol. 14, no. 11, pp. 3144–3161, 2019, [Online]. Available at: https://rdcu.be/bRSze.
    https://rdcu.be/bRSze
  5. L. Robert, J. Ollion, J. Robert, X. Song, I. Matic, and M. Elez, “Mutation dynamics and fitness effects followed in single cells,” Science, vol. 359, no. 6381, pp. 1283–1286, 2018, [Online]. Available at: https://science.sciencemag.org/content/359/6381/1283.editor-summary.
    https://science.sciencemag.org/content/359/6381/1283.editor-summary
  6. J. Ollion, F. Loll, J. Cochennec, T. Boudier, and C. Escudé, “Proliferation-dependent positioning of individual centromeres in the interphase nucleus of human lymphoblastoid cell lines,” Molecular biology of the cell, vol. 26, no. 13, pp. 2550–2560, 2015, [Online]. Available at: https://www.molbiolcell.org/doi/full/10.1091/mbc.E14-05-1002.
    https://www.molbiolcell.org/doi/full/10.1091/mbc.E14-05-1002
  7. J. Ollion, J. Cochennec, F. Loll, C. Escudé, and T. Boudier, “Analysis of nuclear organization with TANGO, software for high-throughput quantitative analysis of 3D fluorescence microscopy images,” in The Nucleus, Springer, 2015, pp. 203–222.
    https://link.springer.com/protocol/10.1007%2F978-1-4939-1680-1_16
  8. J. Ollion, J. Cochennec, F. Loll, C. Escudé, and T. Boudier, “TANGO: a generic tool for high-throughput 3D image analysis for studying nuclear organization,” Bioinformatics, vol. 29, no. 14, pp. 1840–1841, 2013, [Online]. Available at: https://academic.oup.com/bioinformatics/article/29/14/1840/231770.
    https://academic.oup.com/bioinformatics/article/29/14/1840/231770

Contact

If you require any further information, feel free to contact me