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36 results on '"Delsuc, Marc-Andre"'

1. Deconvolution of isotopic pattern in 2D-FTICR Mass Spectrometry of peptides and proteins

Author

Duciel, Laura, Cherni, Afef, and Delsuc, Marc-André

Subjects
Physics - Chemical Physics
Abstract

Mass Spectrometry (MS) is a largely used analytical technique in biology with applications such as the determination of molecule masses or the elucidation of structural data. Fourier Transform Ion Cyclotron Resonance MS is one implementation of the technique allowing high resolution and mass accuracy and based on trapping ions in circular orbits thanks to powerful Electromagnetic fields. This method has been extended to two-dimensional analysis, this gives signals containing a lot more information, for a reasonable amount of time and samples. However, the data provided by such experiments cannot be stored in a classical manner and require some tools and architecture to store and compress data so that they remain accessible and usable without necessitating too much computer memory. The developed python program permits to turn these huge raw data into exploitable FTICR MS HDF5 formatted datasets which can be relatively rapidly and efficiently deconvolved and analysed using a Primal-Dual Splitting algorithm., Comment: 16 pages, 3 figures

Published
2019

2. Automatic differential analysis of NMR experiments in complex samples

Author

Margueritte, Laure, Markov, Petar, Chiron, Lionel, Starck, Jean-Philippe, Vonthron-Sénécheau, Catherine, Bourjot, Mélanie, and Delsuc, Marc-André

Subjects
Physics - Chemical Physics
Abstract

Liquid state NMR is a powerful tool for the analysis of complex mixtures of unknown molecules. This capacity has been used in many analytical approaches: metabolomics, identification of active compounds in natural extracts, characterization of species, and such studies require the acquisition of many diverse NMR measurements on series of samples. While acquisition can easily be performed automatically, the number of NMR experiments involved in these studies increases very rapidly and this data avalanche requires to resort to automatic processing and analysis. We present here a program that allows the autonomous, unsupervised processing of a large corpus of 1D, 2D and DOSY experiments from a series of samples acquired in different conditions. The program provides all the signal processing steps, as well as peak-picking and bucketing of 1D and 2D spectra, the program and its components are fully available. In an experiment mimicking the search of an active species in natural extract, we use it for the automatic detection of small amounts of artemisin added to a series of plant extracts, and for the generation of the spectral fingerprint of this molecules. This program called Plasmodesma is a novel tool which should be useful to decipher complex mixtures, particularly in the discovery of biologically active natural products from plants extracts, but can also in drug discovery or metabolomics studies., Comment: 35 pages, 36 figures, 26 references

Published
2017

3. Sustainable computational science: the ReScience initiative

Author

Rougier, Nicolas P., Hinsen, Konrad, Alexandre, Frédéric, Arildsen, Thomas, Barba, Lorena, Benureau, Fabien C. Y., Brown, C. Titus, de Buyl, Pierre, Caglayan, Ozan, Davison, Andrew P., Delsuc, Marc André, Detorakis, Georgios, Diem, Alexandra K., Drix, Damien, Enel, Pierre, Girard, Benoît, Guest, Olivia, Hall, Matt G., Henriques, Rafael Neto, Hinaut, Xavier, Jaron, Kamil S, Khamassi, Mehdi, Klein, Almar, Manninen, Tiina, Marchesi, Pietro, McGlinn, Dan, Metzner, Christoph, Petchey, Owen L., Plesser, Hans Ekkehard, Poisot, Timothée, Ram, Karthik, Ram, Yoav, Roesch, Etienne, Rossant, Cyrille, Rostami, Vahid, Shifman, Aaron, Stachelek, Joseph, Stimberg, Marcel, Stollmeier, Frank, Vaggi, Federico, Viejo, Guillaume, Vitay, Julien, Vostinar, Anya, Yurchak, Roman, and Zito, Tiziano

Subjects
Computer Science - Digital Libraries
Abstract

Computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing results, however computational science lags behind. In the best case, authors may provide their source code as a compressed archive and they may feel confident their research is reproducible. But this is not exactly true. James Buckheit and David Donoho proposed more than two decades ago that an article about computational results is advertising, not scholarship. The actual scholarship is the full software environment, code, and data that produced the result. This implies new workflows, in particular in peer-reviews. Existing journals have been slow to adapt: source codes are rarely requested, hardly ever actually executed to check that they produce the results advertised in the article. ReScience is a peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research can be replicated from its description. To achieve this goal, the whole publishing chain is radically different from other traditional scientific journals. ReScience resides on GitHub where each new implementation of a computational study is made available together with comments, explanations, and software tests., Comment: 8 pages, 1 figure

Published
2017
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4. PALMA, an improved algorithm for DOSY signal processing

Author

Cherni, Afef, Chouzenoux, Emilie, and Delsuc, Marc-André

Subjects
Physics - Data Analysis, Statistics and Probability
Abstract

NMR is a tool of choice for the measure of diffusion coefficients of species in solution. The DOSY experiment, a 2D implementation of this measure, has proven to be particularly useful for the study of complex mixtures, molecular interactions, polymers, etc. However, DOSY data analysis requires to resort to inverse Laplace transform, in particular for polydisperse samples. This is a known difficult numerical task, for which we present here a novel approach. A new algorithm based on a splitting scheme and on the use of proximity operators is introduced. Used in conjunction with a Maximum Entropy and $\ell_1$ hybrid regularisation, this algorithm converges rapidly and produces results robust against experimental noise. This method has been called PALMA. It is able to reproduce faithfully monodisperse as well as polydisperse systems, and numerous simulated and experimental examples are presented. It has been implemented on the server http://palma.labo.igbmc.fr where users can have their datasets processed automatically., Comment: 23 pages, 9 figures revised version, with new examples

Published
2016
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5. SPIKE a Processing Software dedicated to Fourier Spectroscopies

Author

Chiron, Lionel, Coutouly, Marie-Aude, Starck, Jean-Philippe, Rolando, Christian, and Delsuc, Marc-André

Subjects
Physics - Computational Physics, Physics - Chemical Physics
Abstract

We present SPIKE (Spectrometry Processing Innovative KErnel), an open-source Python package dedicated to Fourier spectroscopies. It provides basic functionalities such as apodisation, a complete set of Fourier transforms, phasing for NMR), peak-picking, baseline correction and also tools such as Linear Prediction. Beside its versatility, the most prominent novelty of this package is to incorporate new tools for Big Data processing. This is exemplified by its ability to handle the processing and visualization of very large data-sets, with multiprocessor capabilities and a low memory footprint. The software contains also all the tools necessary for the specific fast processing and visualization of 2D-FTICR-MS data-sets., Comment: 13 pages, 4 figures

Published
2016

6. Accurate DOSY measure of out-of-equilibrium systems by permutated DOSY (p-DOSY)

Author

Oikonomou, Maria, Hernández, Julia Asencio, Velders, Aldrik H., and Delsuc, Marc-André

Subjects
Physics - Chemical Physics
Abstract

NMR spectroscopy is an excellent tool for monitoring in-situ chemical reactions. In particular, DOSY measurement is well suited to characterize transient species by the determination of their sizes. However, here we bring to light a difficulty in the DOSY experiments performed in out-of-equilibrium systems. On such a system, the evolution of the concentration of species interferes with the measurement process, and creates a bias on the diffusion coefficient determination that may lead to erroneous interpretations. We show that a random permutation of the series of gradient strengths used during the DOSY experiment allows to average out this bias. This approach, that we name p-DOSY does not require changes in the the pulse sequences nor in the processing software, and restores completely the full accuracy of the measure. This technique is demonstrated on the monitoring of the anomerization reaction of \alpha- to \beta-glucose., Comment: Revised version - 15 pages, 8 figures program archived at 10.5281/zenodo.19261

Published
2015
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8. RamaDA: complete and automated conformational overview of proteins

Author

Tanty, Matthieu and Delsuc, Marc-André

Subjects
Quantitative Biology - Biomolecules, Quantitative Biology - Quantitative Methods
Abstract

The tertiary structure of protein, as well as the local secondary structure organization are fully determined by the angles of the peptidic bound. The backbone dihedral angles not only determine the global fold of the protein, but also the details of the local chain organization. Although a wealth of structural information is available in different databases and numerous structural biology softwares have been developed, rapid conformational characterization remains challenging. We present here RamaDA, a program able to give a synthetic description of the conformation of a protein. The RamaDA program is based on a model where the Ramachadran plot is decomposed into seven conformational domains. Within the framework of this model, each amino-acid of a given protein is assigned to one of these domains. From this assignment secondary structure elements can be detected with an accuracy equivalent to that of the DSSP program for helices and extended strands, and with the added capability of detecting PolyProline II secondary structures. Additionally, the determination of a z-score for each amino-acid of the protein emphasizes any irregularities in the element. It is also possible to use this analysis to detect characteristic conformational patterns. In the case of EF-hands, calcium-binding helix-loop-helix domains, it is possible to design a strict consensus for the 9 amino-acids of the loop. 523 calcium binding protein files can be found into the entire PDB with this pattern and only 2.7% false positive hits are detected. The program RamaDA gathers several tools in one and is then able to give a complete information on a protein structure, including loops and random coil regions. Through the example of EF-hands, a promising approach of structural biology is developed. RamaDA is freely available for download as well as online usage at http://ramada.u-strasbg.fr, Comment: 7 pages, 3 figures, 3 tables

Published
2011

18. Alpha-cobratoxin: proton NMR assignments and solution structure

Author

Le Goas, Remi, LaPlante, Steven R., Mikou, Afaf, Delsuc, Marc-Andre, Guittet, Eric, Robin, Michel, Charpentier, Isabelle, and Lallemand, Jean-Yves

Subjects
Neurotoxic agents -- Research, Nuclear magnetic resonance spectroscopy -- Usage, Biological sciences, Chemistry
Abstract

Research was conducted on alpha-cobratoxin usingproton nuclear magnetic resonance spectroscopy. Results revealed the existence of a triple-stranded beta-sheet, a short helix and turns in the solution structure of alpha-cobratoxin. Further observations also revealed a similarity between the solution and crystal structures of alpha-cobratoxin.

Published
1992

20. Fast Dictionary-Based Approach for Mass Spectrometry Data Analysis

Author

Cherni Afef, Chouzenoux Emilie, Delsuc Marc-Andre, Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), and Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Computer science, 020206 networking & telecommunications, Context (language use), 02 engineering and technology, [INFO.INFO-NA]Computer Science [cs]/Numerical Analysis [cs.NA], Mass spectrometry, Matrix (mathematics), Superposition principle, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, Convex optimization, 0202 electrical engineering, electronic engineering, information engineering, DECIPHER, [CHIM]Chemical Sciences, [INFO]Computer Science [cs], Limit (mathematics), [MATH]Mathematics [math], Circulant matrix, Algorithm, ComputingMilieux_MISCELLANEOUS, Block (data storage)
Abstract

Mass spectrometry (MS) is a fundamental technology of analytical chemistry for measuring the structure of molecules, with many application fields such as clinical biomarker analysis or pharmacokinetics. In the context of proteomic analysis with MS, the superposition of the isotopic patterns of different proteins, in various charge-states produces MS spectra difficult to decipher. The complexity of the pattern models and the large size of the data again increase the difficulty of the analysis step. In this paper, we propose to formulate the problem of proteins characterization as the estimation of a positive-valued sparse signal thanks to a dictionary-based approach relying on the protein averagine concept. A proximal primal-dual splitting convex optimization method is considered to solve the resulting variational problem. Moreover, the large size of the dictionary matrix is circumvented by proposing a suitable block circulant approximation of it, allowing to limit the computational burden of the method. Numerical experiments on synthetic and real MS datasets illustrate the good performance of our approach.

Published
2018
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24. Sustainable computational science: the ReScience initiative

Author

Rougier, Nicolas P, Hinsen, Konrad, Alexandre, Frederic, Arildsen, Thomas, Barba, Lorena A, Benureau, Fabien C.Y, Brown, C. Titus, deBuy, Pierre, Caglayan, Ozan, Davison, Andrew P., Delsuc, Marc-Andre, Detorakis, Georgios, Diem, Alexandra, Drix, Damien, Enel, Pierre, Girard, Benoit, Guest, Olivia, Hall, Matt G, Henriques, Rafael N, Hinaut, Xavier, Jaron, Kamil S, Khamassi, Mehdi, Klein, Almar, Manninen, Tiina, Marchesi, Pietro, McGlinn, Daniel, Metzner, Christoph, Petchey, Owen, Plesser, Hans Ekkehard, Poisot, Timothee, Ram, Karthik, Ram, Yoav, Roesch, Etienne, Rossant, Cyrille, Rostami, Vahid, Shifman, Aaron, Stachelek, Joseph, Stimberg, Marcel, Stollmeier, Frank, Vaggi, Federico, Viejo, Guillaume, Vitay, Julien, Vostinar, Anya E, Yurchak, Roman, Zito, Tiziano, Mnemonic Synergy ( Mnemosyne ), Laboratoire Bordelais de Recherche en Informatique ( LaBRI ), Centre National de la Recherche Scientifique ( CNRS ) -École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Université Sciences et Technologies - Bordeaux 1-Université Bordeaux Segalen - Bordeaux 2-Centre National de la Recherche Scientifique ( CNRS ) -École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Université Sciences et Technologies - Bordeaux 1-Université Bordeaux Segalen - Bordeaux 2-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut des Maladies Neurodégénératives [Bordeaux] ( IMN ), Université de Bordeaux ( UB ) -Centre National de la Recherche Scientifique ( CNRS ) -Université de Bordeaux ( UB ) -Centre National de la Recherche Scientifique ( CNRS ), Centre de biophysique moléculaire ( CBM ), Université d'Orléans ( UO ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Department of Electronic Systems - Aalborg University, Aalborg University [Denmark] ( AAU ), Washington State University ( WSU ), CIM - Communication, Information, Médias - EA 1484 ( CIM ), Université Sorbonne Nouvelle - Paris 3, Université Libre de Bruxelles [Bruxelles] ( ULB ), Laboratoire d'Informatique de l'Université du Mans ( LIUM ), Le Mans Université ( UM ), Ecole des Neurosciences de Paris Île de France ( ENP ), Ecole des Neurosciences de Paris, Centre de Biochimie Structurale [Montpellier] ( CBS ), Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Université de Montpellier ( UM ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire des signaux et systèmes ( L2S ), Université Paris-Sud - Paris 11 ( UP11 ) -CentraleSupélec-Centre National de la Recherche Scientifique ( CNRS ), University of Southampton [Southampton], Humboldt Universität zu Berlin, Institut cellule souche et cerveau / Stem Cell and Brain Research Institute ( SBRI ), Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Laboratoire de Physiologie de la Perception et de l'Action ( LPPA ), Collège de France ( CdF ) -Centre National de la Recherche Scientifique ( CNRS ), Institut des Systèmes Intelligents et de Robotique ( ISIR ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Centre National de la Recherche Scientifique ( CNRS ), University of Oxford [Oxford], University College of London [London] ( UCL ), Instituto de Medicina Molecular, Faculdade de Medicina da Universidade de Lisboa, Knowledge Technology group [Hamburg] ( KT ), Department of Informatics [Hamburg], Universität Hamburg ( UHH ) -Universität Hamburg ( UHH ), Université de Lausanne ( UNIL ), National Coalition of Independent Scholar ( NCIS ), Finnish Meteorological Institute ( FMI ), Vrije Universiteit Amsterdam [Amsterdam] ( VU ), Department of Biology [Charleston], College of Charleston, Universität Zürich [Zürich] ( UZH ), University of Zürich [Zürich] ( UZH ), Institute of Neuroscience and Medicine [Jülich] ( INM-1 ), Université de Montréal, University of California [Berkeley], Department of Biological Sciences [Stanford], Stanford University [Stanford], Department of Psychology, University of Geneva [Switzerland], Swiss Center for Affective Sciences, University of Ottawa [Ottawa], Michigan State University [East Lansing], Institut de la Vision, Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Institut d'études de la cognition ( IEC ), Département d'Etudes Cognitives - ENS Paris ( DEC ), École normale supérieure - Paris ( ENS Paris ) -École normale supérieure - Paris ( ENS Paris ), Max Planck Institute of Experimental Medicine [Göttingen] ( MPI ), Statistical Machine Learning and Parsimony ( SIERRA ), Département d'informatique de l'École normale supérieure ( DI-ENS ), École normale supérieure - Paris ( ENS Paris ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Centre National de la Recherche Scientifique ( CNRS ) -École normale supérieure - Paris ( ENS Paris ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Centre National de la Recherche Scientifique ( CNRS ) -Centre National de la Recherche Scientifique ( CNRS ) -Inria de Paris, Institut National de Recherche en Informatique et en Automatique ( Inria ), Chemnitz University of Technology, Grinnell College, Laboratoire pour l'utilisation des lasers intenses ( LULI ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -École polytechnique ( X ) -Université Paris-Saclay-Centre National de la Recherche Scientifique ( CNRS ), Eberhard Karls Universität Tübingen, Mnemonic Synergy (Mnemosyne), Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut des Maladies Neurodégénératives [Bordeaux] (IMN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Centre de biophysique moléculaire (CBM), Université d'Orléans (UO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Aalborg University [Denmark] (AAU), Washington State University (WSU), University of California [Davis] (UC Davis), University of California (UC), Université libre de Bruxelles (ULB), Laboratoire d'Informatique de l'Université du Mans (LIUM), Le Mans Université (UM), Ecole des Neurosciences de Paris Île de France (ENP), Centre de Biochimie Structurale [Montpellier] (CBS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire des signaux et systèmes (L2S), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), University of Southampton, Humboldt University Of Berlin, Institut cellule souche et cerveau (SBRI), Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire de Physiologie de la Perception et de l'Action (LPPA), Collège de France (CdF (institution))-Centre National de la Recherche Scientifique (CNRS), Institut des Systèmes Intelligents et de Robotique (ISIR), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), AMAC, Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), University of Oxford, University College of London [London] (UCL), Instituto de Medicina Molecular (iMM), Faculdade de Medicina [Lisboa], Universidade de Lisboa = University of Lisbon (ULISBOA)-Universidade de Lisboa = University of Lisbon (ULISBOA), Knowledge Technology group [Hamburg] (KT), University of Hamburg-University of Hamburg, Université de Lausanne = University of Lausanne (UNIL), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), National Coalition of Independent Scholar (NCIS), Finnish Meteorological Institute (FMI), Vrije Universiteit Amsterdam [Amsterdam] (VU), Universität Zürich [Zürich] = University of Zurich (UZH), Institute of Neuroscience and Medicine [Jülich] (INM-1), Université de Montréal (UdeM), Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Department of Biology [Stanford], Stanford University, Université de Genève = University of Geneva (UNIGE), Swiss Center for Affective Sciences (CISA), Michigan State University System, Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Labex Institut d'étude de la cognition (IEC), Département d'Etudes Cognitives - ENS Paris (DEC), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Max Planck Institute of Experimental Medicine [Göttingen] (MPI), Max-Planck-Gesellschaft, Statistical Machine Learning and Parsimony (SIERRA), Département d'informatique - ENS Paris (DI-ENS), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria), Chemnitz University of Technology / Technische Universität Chemnitz, Laboratoire pour l'utilisation des lasers intenses (LULI), Université Pierre et Marie Curie - Paris 6 (UPMC)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS), Eberhard Karls Universität Tübingen = Eberhard Karls University of Tuebingen, Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Inria Bordeaux - Sud-Ouest, Université d'Orléans (UO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC), University of California, Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Institut National de la Santé et de la Recherche Médicale (INSERM), Humboldt-Universität zu Berlin, Institut cellule souche et cerveau (U846 Inserm - UCBL1), Universidade de Lisboa (ULISBOA)-Universidade de Lisboa (ULISBOA), Université de Lausanne (UNIL), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Inria de Paris, Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC), Département d'informatique de l'École normale supérieure (DI-ENS), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), and Rougier, Nicolas P.

Subjects
FOS: Computer and information sciences, Technology, Journal, lcsh:QA75.5-76.95, Computational Science, GitHub, Scientific Computing and Simulation, Social Computing, Open Science, Replicability, REPRODUCIBLE RESEARCH, [INFO.INFO-DL]Computer Science [cs]/Digital Libraries [cs.DL], Open peer-review, Digital Libraries (cs.DL), Computational science, Open science, Publication, Reproducible, Replicable, Sustainable, GitHub, Open peer-review, [ INFO.INFO-DL ] Computer Science [cs]/Digital Libraries [cs.DL], Science & Technology, Computer Science, Information Systems, Data Science, Computational science, bepress|Physical Sciences and Mathematics|Computer Sciences, Computer Science - Digital Libraries, Sustainable, Reproducibility, Networking and Information Technology R&D (NITRD), Digital Libraries, Computer Science, Reproducible, Publication, Open science, lcsh:Electronic computers. Computer science, [INFO.INFO-DL] Computer Science [cs]/Digital Libraries [cs.DL], Replicable
Abstract

Computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing results, however computational science lags behind. In the best case, authors may provide their source code as a compressed archive and they may feel confident their research is reproducible. But this is not exactly true. James Buckheit and David Donoho proposed more than two decades ago that an article about computational results is advertising, not scholarship. The actual scholarship is the full software environment, code, and data that produced the result. This implies new workflows, in particular in peer-reviews. Existing journals have been slow to adapt: source codes are rarely requested, hardly ever actually executed to check that they produce the results advertised in the article. ReScience is a peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research can be replicated from its description. To achieve this goal, the whole publishing chain is radically different from other traditional scientific journals. ReScience resides on GitHub where each new implementation of a computational study is made available together with comments, explanations, and software tests., 8 pages, 1 figure

Published
2017
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25. Molecular weights of cyclic and hollow clusters measured by DOSY NMR spectroscopy

Author

Floquet, Sebastien, Brun, Sebastien, Lemonnier, Francois, Henry, Marc, Delsuc, Marc-Andre, Prigent, Yann, Cadot, Emmanuel, and Taulelle, Francis

Subjects
Diffusion processes -- Analysis, Hydrodynamics -- Analysis, Nuclear magnetic resonance spectroscopy -- Usage, Hydrofoil boats -- Hydrodynamics, Hydrofoil boats -- Analysis, Chemistry
Abstract

The Stokes-Einstein expression of the diffusion coefficient as a function of the hydrodynamic radius of the diffusing object has not carried the mass dependency of the object, but the translational self-diffusion coefficients D are correlated with the molecular weight M for an ensemble of cyclic or hollow clusters. The correlation has shown that the mass of a cluster is deduced from its diffusion coefficient.

Published
2009

26. NMR measure of translational diffusion and fractal dimension. application to molecular mass measurement

Author

Auge, Sophie, Schmit, Pierre-Olivier, Crutchfield, Christopher A., Islam, Mohammad T., Harris, Douglas J., Durand, Emmanuelle, Clemancey, Martin, Quoineaud, Anne-Agathe, Lancelin, Jean-Marc, Prigent, Yann, Taulelle, Francis, and Delsuc, Marc-Andre

Subjects
Diffusion -- Research, Nuclear magnetic resonance -- Usage, Polymers -- Research, Proteins -- Research, Chemicals, plastics and rubber industries
Published
2009

27. Proximity operators for a class of hybrid sparsity + entropy priors application to dosy NMR signal reconstruction

Author

Cherni Afef, Chouzenoux Emilie, and Delsuc Marc-Andre

Subjects
Mathematical optimization, Laplace inversion, Optimization algorithm, Signal reconstruction, Principle of maximum entropy, Prior probability, Entropy (information theory), Inverse problem, Laplace transform inversion, Mathematics
Abstract

Inverse problems arising from Laplace transform inversion are ill-posed, and require suitable regularization strategies. Although the maximum entropy regularization approach usually appears as an adequate strategy due to its ability to recover regular positive valued signals, it was observed to lead to poor reconstruction results when the sought signal contains narrow peaks. In that case, a sparsity promoting penalty such as the h norm, combined with a positivity constraint, is more suitable. In order to derive a flexible resolution method, hybrid approaches combining both entropy and sparsity regularization strategies should be envisaged. However, the choice of an efficient optimization algorithm remains a challenging task. Among available optimization techniques, proximal methods have shown their efficiency in solving large scale possibly nonsmooth problems. This paper provides an extensive list of new proximity operators for the sum of entropy and sparsity penalties. The applicability of these results is illustrated by means of experiments, in the context of DOSY NMR signal reconstruction.

Published
2016
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28. Active peptidic mimics of the second intracellular loop of the V (sub)1A vasopressin receptor are structurally related to the second intracellular rhodopsin loop: a combined (super)1 H NMR and biochemical study

Author

Demene, Helene, Granier, Sebastien, Muller, Dany, Gillon, Gilles, Dufour, Marie-Noelle, Delsuc, Marc-Andre, Hibert, Marcel, Pascal, Robert, and Mendre, Christiane

Subjects
Chemical inhibitors -- Physiological aspects, G proteins -- Physiological aspects, Nuclear magnetic resonance spectroscopy -- Usage, Rhodopsin -- Physiological aspects, Vasopressin -- Physiological aspects, Peptides -- Physiological aspects, Biochemistry -- Research, Biological sciences, Chemistry
Abstract

Research has been conducted on vasopressin receptors which belong to G protein-coupled receptor family. The authors have synthesized the linear and cyclic forms of the second intracellular loop of human vasopressin receptor isoform in the effort to investigate the interactions between (alpha)q/(alpha)11 G protein and receptor, and they report that these two peptides inhibit vasopressin binding to the human vasopressing receptor.

Published
2003

29. Storing the portrait of Antoine de Lavoisier in a single macromolecule

Author

Laurent, Eline, Amalian, Jean-Arthur, Schutz, Thibault, Launay, Kevin, Clément, Jean-Louis, Gigmes, Didier, Burel, Alexandre, Carapito, Christine, Charles, Laurence, Delsuc, Marc-André, and Lutz, Jean-François

Subjects
Sequence-controlled polymers, Digital polymers, Information-containing macromolecules, Solid-phase synthesis, Mass spectrometry sequencing, Biochemistry, QD415-436, Physical and theoretical chemistry, QD450-801, Mathematics, QA1-939
Abstract

A pixelated portrait of Antoine de Lavoisier was stored in a digitally-encoded poly(phosphodiester). The storage capacity attained in this work (440 bits/chain) is the highest ever reported for a synthetic informational polymer. To reach this very high capacity, a combination of data compression and polymer design was used. For instance, the digital polymer was synthesized by automated phosphoramidite chemistry using an optimized set of nineteen building blocks (8 coded monomers, 10 mass tags and one alkoxyamine linker enabling decryption by tandem mass spectrometry). Consequently, the polymer could be comprehensively decoded by electrospray mass spectrometry and the portrait of the French chemist was recovered.

Published
2021
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