Xavier Brochet

TL;DR: IMIMGT (cid:1) as discussed by the authors is a high-quality integrated knowledge resource specialized in the immunoglobulins or antibodies, T cell receptors, major histocompatibility complex, of human and other vertebrate species, proteins of the IgSF and MhcSF, and related proteins of any spe-cies.

TL;DR: In this paper , an approach that combines metabarcoding data and machine learning algorithms to identify potential stressors of soil protist community composition and diversity was proposed. But the most responsive taxa were found within the clades Rhizaria and Alveolata, suggesting that protists are particularly responsive to stresses caused by these variables.

TL;DR: Common sequences among ground-level clusters enabled grouping into clearly delineated, higher-order clusters that were considerably larger in size and displayed ‘CLL-biased’ features with regard to: IGHV gene usage, somatic hypermutation and VH CDR3 pattern composition.

TL;DR: Promising results showed that the use of deep learning methodologies allows genetic modification of phages to extend, for instance, their host range, confirming the potential of these approaches to guide bacteriophage engineering.