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Christophe Bruley

dblp:02/2967 · DBLP profile ↗
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4ranked-venue papers
0as first author
0since 2021 · last 2020
0000-0003-2155-1234ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 3Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
3 papers
Bioinformatics and computational biology · 100%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
proteomics
0.832020
Proline: an efficient and user-friendly software suite for large-scale proteomics · Bioinform. 2020
DAPAR & ProStaR: software to perform statistical analyses in quantitative discovery proteomics · Bioinform. 2017
A toolbox for validation of mass spectrometry peptides identification and generation of database: IRMa · Bioinform. 2009
Bioinformatics and computational biology › proteomics
mass spectrometry data analysis
0.412020
Proline: an efficient and user-friendly software suite for large-scale proteomics · Bioinform. 2020
Bioinformatics and computational biology › computational microbiology › microbiome analysis
differential abundance testing
0.312017
DAPAR & ProStaR: software to perform statistical analyses in quantitative discovery proteomics · Bioinform. 2017
Bioinformatics and computational biology › proteomics
quantitative proteomics
0.312017
DAPAR & ProStaR: software to perform statistical analyses in quantitative discovery proteomics · Bioinform. 2017
Bioinformatics and computational biology › proteomics › quantitative proteomics
label-free quantification
0.112020
Proline: an efficient and user-friendly software suite for large-scale proteomics · Bioinform. 2020

Methods — techniques the papers use, named apart from their topics

DDA label-free quantification · 0.4peptide intensity aggregation · 0.3null hypothesis significance testing · 0.3normalization · 0.3imputation · 0.3false discovery rate · 0.3mascot search · 0.1
YearPublicationVenuePosition
2020 Proline: an efficient and user-friendly software suite for large-scale proteomics
abstract
MOTIVATION: The proteomics field requires the production and publication of reliable mass spectrometry-based identification and quantification results. Although many tools or algorithms exist, very few consider the importance of combining, in a unique software environment, efficient processing algorithms and a data management system to process and curate hundreds of datasets associated with a single proteomics study. RESULTS: Here, we present Proline, a robust software suite for analysis of MS-based proteomics data, which collects, processes and allows visualization and publication of proteomics datasets. We illustrate its ease of use for various steps in the validation and quantification workflow, its data curation capabilities and its computational efficiency. The DDA label-free quantification workflow efficiency was assessed by comparing results obtained with Proline to those obtained with a widely used software using a spiked-in sample. This assessment demonstrated Proline's ability to provide high quantification accuracy in a user-friendly interface for datasets of any size. AVAILABILITY AND IMPLEMENTATION: Proline is available for Windows and Linux under CECILL open-source license. It can be deployed in client-server mode or in standalone mode at http://proline.profiproteomics.fr/#downloads. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
David Bouyssié, Anne-Marie Hesse, Emmanuelle Mouton-Barbosa, Magali Rompais, Charlotte Macron, Christine Carapito, Anne Gonzalez de Peredo, Yohann Couté, Véronique Dupierris, Alexandre Burel, Jean-Philippe Menetrey, Andrea Kalaitzakis, Julie Poisat, Aymen Romdhani, Odile Burlet-Schiltz, Sarah Cianférani, Jerome Garin, Christophe Bruley
Bioinform.18
2017 DAPAR & ProStaR: software to perform statistical analyses in quantitative discovery proteomics
abstract
DAPAR and ProStaR are software tools to perform the statistical analysis of label-free XIC-based quantitative discovery proteomics experiments. DAPAR contains procedures to filter, normalize, impute missing value, aggregate peptide intensities, perform null hypothesis significance tests and select the most likely differentially abundant proteins with a corresponding false discovery rate. ProStaR is a graphical user interface that allows friendly access to the DAPAR functionalities through a web browser. AVAILABILITY AND IMPLEMENTATION: DAPAR and ProStaR are implemented in the R language and are available on the website of the Bioconductor project (http://www.bioconductor.org/). A complete tutorial and a toy dataset are accompanying the packages. CONTACT: [email protected], [email protected], [email protected].
Samuel Wieczorek, Florence Combes, Cosmin Lazar, Quentin Giai Gianetto, Laurent Gatto, Alexia Dorffer, Anne-Marie Hesse, Yohann Couté, Myriam Ferro, Christophe Bruley, Thomas Burger
Bioinform.10
2009 A toolbox for validation of mass spectrometry peptides identification and generation of database: IRMa
abstract
SUMMARY: The IRMa toolbox provides an interactive application to assist in the validation of Mascot search results. It allows automatic filtering of Mascot identification results as well as manual confirmation or rejection of individual PSM (a match between a fragmentation mass spectrum and a peptide). Dynamic grouping and coherence of information are maintained by the software in real time. Validated results can be exported under various forms, including an identification database (MSIdb). This allows biologists to compile search results from a whole study in a unique repository in order to provide a summarized view of their project. IRMa also features a fully automated version that can be used in a high-throughput pipeline. Given filter parameters, it can delete hits with no significant PSM, regroup hits identified by the same peptide(s) and export the result to the specified format without user intervention. AVAILABILITY: http://biodev.extra.cea.fr/docs/irma (java 1.5 or higher needed).
Véronique Dupierris, Christophe Masselon, Magali Court, Sylvie Kieffer-Jaquinod, Christophe Bruley
Bioinform.5
2001 A New Approach in Object-Based Knowledge Representation: The AROM System
Michel Page, Jérôme Gensel, Cécile Capponi, Christophe Bruley, Philippe Genoud, Danielle Ziébelin, Daniel Bardou, Véronique Dupierris
IEA/AIE4