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2018
Previous editions: 2017 | 2016 | 2015 | 2014
Laurent Heirendt, Ph.D.

University of Luxembourg



COBRA.jl - Gearing up for high-dimensional constraint-based modelling

The COnstraint-Based Reconstruction and Analysis (COBRA) community is developing ever larger biochemical networks. Reconstructions with millions of biochemical reactions are on the horizon. The limits of traditional implementations in MATLAB, Python, or C, are reached when exploring such large networks, especially when performing the same analysis on thousands of these large models. A main requirement for accelerating existing and new COBRA methods is a short development time and the ability to gain speedups with the convenience of writing code similar to Python or MATLAB while assuring parallelism across multiple nodes without traditional MPI- based languages. This is why the COBRA community turned towards Julia, and released the high-level, high-performance, and open-source COBRA.jl package. DistributedFBA.jl [1], part of COBRA.jl, allows to perform a flux variability analysis or any of its related types efficiently, especially on large (up to 500’000 reactions) and huge-scale models (more than 500’000 reactions). PALM.jl [2] allows to launch analyses based on the COBRA Toolbox [3] across several computing nodes simultaneously, and this for hundreds of models. The COBRA Toolbox is a comprehensive software suite of interoperable COBRA methods written in MATLAB, which has found widespread applications in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. Julia is the language of choice when it comes to accelerating analyses of large and huge-scale biochemical networks. With the COBRA.jl package, reconstruction and analysis of large and huge-scale models is made possible and accelerated.

Speaker's bio

Laurent Heirendt was born in 1987 in Luxembourg City, Luxembourg (Europe). He received his BSc in Mechanical Engineering from the Ecole Polytechnique Fédérale de Lausanne, Switzerland in 2009. A year later, he received his MSc in Advanced Mechanical Engineering from Imperial College London in the UK, where his research and thesis focused on developing a general dynamic model for shimmy analysis of aircraft landing gear that is still in use today. He received his Ph.D. in 2014 in Aerospace Science from the University of Toronto, Canada. He developed a thermo-tribomechnical model of an aircraft landing gear, which led to a patent pending design of a critical aircraft landing gear component. He then worked in industry and oversaw the structural analysis of large aircraft docking structures. Recently, Laurent started as a Research Associate at the Luxembourg Centre for Systems Biomedicine, where he works in the numerical optimization of large biochemical networks using Julia. Besides his mother tongue Luxembourgish, he is fluent in English, French, and German, and he is currently learning Brazilian Portuguese.