Several members of LCQB co-authored « Meet-U: educating through research immersion », which appeared in PLOS Computational Biology on 03/15/2018. Meet-U is a new educational initiative that aims to train students for collaborative work in computational biology and to bridge the gap between education and research. Meet-U mimics the setup of collaborative research projects and takes advantage of the most popular tools for collaborative work and of cloud computing. Students are grouped in teams of 4–5 people and have to realize a project from A to Z that answers a challenging question in biology. In this paper, we report on our experience with Meet-U in two French universities with master’s students in bioinformatics and modeling, and with protein–protein docking as the subject of the course.
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"A protein coevolution method uncovers critical features of the Hepatitis C Virus fusion mechanism" appeared in PLoS Pathogens, from A.Carbone team. This work sheds light on important structural features of the HCV fusion mechanism and contributes to advance our functional understanding of this process. This study also provides an important proof of concept that coevolution can be employed to explore viral protein mediated-processes, and can guide the development of innovative translational strategies against challenging human-tropic viruses.
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F.Nadalin and A.Carbone published CIPS, a new computational method for scoring protein docking decoys based on a combination of residue-residue contact preferences and interface compositional bias. CIPS outperforms state-of-the-art methods on screening protein-protein docking models and improves the ranking on 28 CAPRI targets. The drastic reduction of candidate solutions produced by thousands of proteins docked against each other makes large-scale docking accessible to analysis.
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Eleonora De Lazzari* published her findings on scaling laws for gene families. A striking quantitative invariant in evolutionary genomics is the scaling with genome size of the number of proteins sharing a specific function. E.D.L. showed that such scaling laws exist systematically at the level of single evolutionary families. This provides a novel view of the links between evolutionary expansion of protein families and gene functions.This work was performed in collaboration with J Grilli (U. Chicago) and S Maslov (U. Illinois).
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Plasmobase is a unique database designed for the comparative study of 11 Plasmodium genomes. Plasmobase proposes new domain architectures as well as new domain families that have never been reported before for these genomes. It allows for an easy comparison among architectures within Plasmodium species and with other species, described in UniProt. Joint work of J.Bernardes and A.Carbone.
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Marco Cosentino-Lagomarsino and Gilles Fischer collaborated with Gianni Liti’s team to generatate end-to-end genome assemblies for 12 yeast genomes based on long-read sequencing. These population-level high-quality genomes with comprehensive annotation enable the first explicit definition of chromosomal boundaries between core and subtelomeric regions as well as a precise quantification of their relative evolutionary rates of genome dynamics.
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The Diatom Functional Genomics Team (Angela Falciatore and Antonio E. Fortunato) contributed to the manuscript “Evolutionary genomics of the cold-adapted diatom Fragilariopsis cylindrus”, published on Nature in January 2017. This study, coordinated by Prof. Thomas Mock, University of East Anglia, Norwich, has revealed the existence of highly diverged alleles in the genome of this polar diatom species that may be involved in adaptation to environmental fluctuations in the Southern Ocean.
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A new publication of F. Devaux Team in NAR:
The discovery of novel specific ribosome-associated factors challenges the assumption that translation relies on standardized molecular machinery. In this work, we demonstrate that Tma108, an uncharacterized translation machinery-associated factor in yeast, is a specific nascent-chain associated factor selectively recruited during the translation of less than 200 mRNAs encoding proteins with ATP or Zinc binding domains. Tma108 is a unique example of a nascent chain-associated factor with high selectivity and its study illustrates the existence of other specific translation-associated factors besides RNA binding proteins.
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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.
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