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 Sorbonne Université.


June 10, 2019

What can proteins tell us about how they interact and function together? At LCQB, we develop computational approaches to predict protein interactions, model protein social behaviour and infer the effect of mutations on protein interaction networks. We just posted this video explaining these ideas to the large public. 

Link to the french video

Link to the italian video

February 3, 2021

Our analysis of "soft disorder" makes the cover of the PLoS Computational Biology January issue.

Link to the paper

October 14, 2020

The first edition of Meet-EU was launched last Friday! Students enrolled in Bioinformatics Master programs from the 4EU+ alliance will join their efforts to predict chromatin organisation from Hi-C data. The LCQB is involved in the organisation of this edition, and in the training of the students!

The full opening session is available at:

July 15, 2020

The new book "Mathematical modelling of evolution. One-locus and multi-locus theory and recombination" by Igor Rouzine appeared in the Mathematical and Life Science Series of De Gruyter. Chp 1. Thought experiments based on a basic model of stochastic evolution of a single genomic site, with random mutation, directional natural selection, and random genetic drift. Chp 2. more advanced theory for a large number of linked loci. Chp 3. Genetic recombination and advantage of sexual reproduction for adaptation.
These models are directly applicable to both asexual and sexual populations, including virus populations in an animal host and a population of hosts.

Link to the book
Link to the book series

May 12, 2020

ANRS communicates today on our new webserver COVTree, designed to predict coevolving residues in overlapping genes and to detect mirrored coevolution.

Link to the article

May 11, 2020

Interested in phylogenetic reconstruction based on synteny rather than protein sequence? PhyChro is out in MBE. This is the last piece of a huge work, CHROnicle , done in collaboration by the Analytical Genomics and the Biology of Genomes teams.

Link to the article


May 10, 2020

Overlapping genes are commonplace in viruses and play an important role in their function and evolution. Coevolution in OVerlapped sequences by Tree analysis (COVTree) is a web server providing the online analysis of coevolving amino-acid pairs in overlapping genes, where residues might be located inside or outside the overlapping region.

Link to the article

May 4, 2020

We propose PhyloSofS, the first automated tool to reconstruct plausible evolutionary scenarios explaining a set of observed transcripts, and to generate 3D molecular models of the protein isoforms. We apply it to the JNK family (60 transcripts, 7 trees) to identify AS events of ancient origin and relate their functional outcome with changes in the protein dynamics. We also show that PhyloSofS can help identify new potential therapeutic targets.

Link to the paper


May 3, 2020

A.Carbone and F.Oteri work on the Spike protein of SARS2 in collaboration with the group of F.L.Cosset at CIRI in Lyon, expert in non-replicative retroviral pseudoparticles. Based on coevolution analysis of patient sequences and sequences from bats and other species, they aim at identifying key residues in the Spike protein involved in the entry mechanism of the virus in human cells. In the past, the two groups successfully combined their computational and experimental methods to unravel critical features of the original HCV fusion mechanism.

May 2, 2020

The team "Statistical Genomics and Biological Physics" has obtained financial support by the Faculty of Sciences and Engineering of Sorbonne Université, to develop sequence-data driven models of evolutionary landscapes and selective constraints acting in the Covid-19 causing virus SARS-CoV-2. The projects aims at finding signatures of selection in the rapidly increasing number of available 
genomes, and to interpret them in terms of protein structure, function and protein-protein interactions inside coronaviruses and with the host (e.g. the famous interaction of the viral spike protein with the human ACE2 receptor).