The Laboratory of Computational and Quantitative Biology (LCQB), headed by A. Carbone, is an interdisciplinary laboratory working at the interface between biology and quantitative sciences. It is built to promote a balanced interaction of theoretical and experimental approaches in biology and to foster the definition of new experimental questions, data analysis and modeling of biological phenomena. Our projects address questions on biological structures and processes through the gathering of experimental measures, the in silico generation of new biological data that remain inaccessible to experiments today (modeling of biological systems), the development of statistical methods for data analysis, and the conception of original algorithms aimed to predictions. The lab is supported by the CNRS and the University Pierre and Marie Curie (UPMC).

News

August 19, 2016

World Community Grid (WCG - IBM) posts a news on our new article appeared in Proteins exploring
data obtained in WCG during the "Help Cure Muscular Dystrophy Project". This work is part of
the MAPPING project (Investissement d'Avenir en Bioinformatique).

To the Article

July 20, 2016

Reviens Avec Tes Prélèvements et analyse les Big Data avec nous

MetaSUB Paris : Cartographier la Diversité Microbienne du Métro Parisien.
An article by Marie Pinhas (UPMC) in french to explain the involvement of the lab in the MetaSUB project. 

July 11-16, 2016

Martin Weigt co-organizes the conference "Statistical physics methods in biology and computer science", a satellite of StatPhys2016, Ecole Normale Superieure, Paris, July 11-16, 2016. It will cover recent progress on the use of methods from statistical mechanics of disordered systems for high dimensional problems related to biology and computer science. Organizers: Simona Cocco, Florent Krzakala, Remi Monasson, Guilhem Semerjian, Martin Weigt, Lenka Zdeborova. 

July 8, 2016

We published a new generation domain annotation approach, demonstrating that "multi-source" domain modelling is more appropriate than "mono-source" domain modelling for capturing remote homology. We re-annotate the Plasmodium falciparum genome.

To the Software

July 5, 2016

F. Devaux's team published one of the first ChIP-seq-based description of the transcriptional regulatory networks in the pathogenic yeast Candida glabrata. This work, which was performed in collaboration with J-M. Camadro and G. Lelandais from the Jacques Monod Institute and with the NGS platform directed by S. Le Crom, is the first publication from a larger ANR project aiming at a comprehensive description of stress response regulatory networks in this emerging human pathogen.

June 27-July 1, 2016

Alessandra Carbone organises with Ion Petre (Turku Centre for Computer Science) the special session "Computation in biological systems" at the international conference "Computability in Europe 2016", Université Paris 7, June 27th 2016 - July 1st 2016

June 21, 2016

On June 21, 2016, LCQB was the Paris Hub for the Global City Sampling Day, an international study of antimicrobial resistance spanning six continents, 32 countries and 54 cities. This event brings together more than 400 people, expected to collect about 12.000 samples of DNA, RNA and microbes from surfaces in well-traveled public meeting spaces. The data will help scientists of the MetaSub Global consortium better understand antimicrobial resistance in urban centers, and also identify new, naturally occurring drugs made by microbes, known as biosynthetic gene clusters. UPMC students in Computer Science and Molecular Biology, together with researchers collected more 80 samples at the entrance of parisian subway stations. The Paris event was organised by Hugues Richard (Analytical Genomics) and Ingrid Lafontaine (Biology of Genomes).

More information on the project: www.metasub.org

June 13-25, 2016

Marco Cosentino Lagomarsino co-organizes the second edition of the workshop: "Quantitative Laws II. From physiology to ecology, from interaction structures to collective behavior".

June 10, 2016

World Community Grid posts a news on Joint Evolutionary Trees 2 (JET2), a new large-scale method to predict protein-protein interfaces based on sequence and structure information.

To the Article and Software.

May 9, 2016

A novel computational approach of coevolution analysis allowed us to reconstruct the protein-protein interaction network of the Hepatitis C Virus at the residue resolution. For the first time, coevolution analysis of an entire viral genome was realized. Champeimont R, Laine E, Hu S-W, Penin F, Carbone A. Coevolution analysis of Hepatitis C virus genome to identify the structural and functional dependency network of viral proteins. Scientific Reports.

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