I hold a permanent PI position at Inria, the French National Institute for Research in Digital Science and Technology. I’m based at the Inria Center at Rennes University, where I’m part of the GenScale project team. I’m also associated with the IRISA Research Institute of Computer Science and Random Systems. Prior to joining Inria in 2022, I was a postdoctoral fellow and a research associate in biomedical informatics and epidemiology at Harvard Medical School and the Harvard T.H. Chan School of Public Health. I received my Ph.D. in computer science from the University of Paris-Est in 2016 and my master’s degree in mathematical computer science from the Czech Technical University in Prague in 2013.
The research of my group focuses on the intersection of computer science and biology, with applications in epidemiology and medicine. We develop novel bioinformatics techniques for DNA data search and analysis, with the ultimate goal of enabling rapid diagnoses of antibiotic resistance at point-of-care settings, better monitoring of the spread of pathogens world-wide, and real-time searching of all publicly deposited DNA sequence data. Our research questions span from the theoretical aspects of computer science to the practical end-to-end protocols used in laboratories. In this context, we are particularly excited about the potential of the emerging rapid and portable genomic technologies, such as nanopore sequencing or CRISPR tests.
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Loren Dejoies, Ph.D.
Visiting Ph.D. student from the Sapienza University of Rome
Visiting MSc. student from the Czech Technical University in Prague (Erasmus)
bioRxiv 2023.04.15.536996, 2023.
Genome Biology 22(96), 2021.
Nature Microbiology 5, pp. 455–464, 2020.
Bioinformatics 31(22), pp. 3584–3592, 2015.
For a full publication list, see Google Scholar.
Framework implementing phylogenetic compression, a technique using evolutionary history to guide compression and efficiently search large collections of microbial genomes using existing algorithms and data structures. This improves the compression ratios of assemblies, de Bruijn graphs, and k-mer indexes by one to two orders of magnitude.
ProphAsm - rapid and memory-efficient computation of simplitigs (spectrum-preserving string sets) and set operations with k-mer sets.
An efficient k-mer index based on the Burrows-Wheeler Transform.
A proof-of-concept framework for Genomic Neighbor Typing for within-minutes predictions of antibiotic resistance during nanopore sequencing. Pipeline, library, two species databases (S. pneumoniae and N. gonorrhoeae), and demonstrations of within-minutes diagnostic from isolates and metagenomes.
Online variant and consensus caller, based on streaming and maintaining variant statistics
in small counters per individual genomic positions, which enables real-time analyzes of
unsorted SAM/BAM data.
A generic format for naming simulated sequencing reads using arbitrary tools and the
associated toolkit and pipeline for read simulation and read mapper evaluation.
Advanced filtering and tagging of SAM/BAM alignments using Python expressions.
Disty McMatrixFace –
Tool for computing a distance matrix from a core genome alignment.
An easy-to-use simulator of nanopore reads, a fork of NanoSim.
For a full software list, see the Github page.
Experimental Bioinformatics; BOX (Fall 2023, Lecturer)
Masters' level course (M1), focused on computational methods for genomics. Taught joinly with Riccardo Vicedomini.
Concepts in Genome Analysis; BMIF 201 (Fall 2019; TA)
PhD level course, focused on quantitative aspects of genetics and genomics, including computational and statistical methods of genomic analysis. Close collaboration with Profs. Shamil R. Sunyaev, Michael Baym, Cheng-Zhong Zhang, and Heng Li.
Assistive Technology; 01ASTE (Falls 2010–2012; Instructor)
Masters' level course.
Software Project; 01SWP1, 01SWP2 (Falls and springs 2010–2012; Supervisor)
Masters' level course.
BBC World Service – Science in Action – 13 Feb 2020
Our paper about rapid diagnostics of antibiotic resistance was covered by BBC World Service in the show Science in Action (13 Feb 2020; starts at 8.10 minutes). 2020-BBC-ScienceInAction-GNT.mp3
The Bioinformatics Chat – Spectrum-preserving string sets and simplitigs – 28 Feb 2020
Our paper about simplitigs for an efficient and scalable representation of de Bruijn graph was covered by the The Bioinformatics Chat podcast series (#42, 28 Feb 2020). 2020-TheBioinformaticsChat-Simplitigs.mp3