MOTIVATION: Infectious diseases persist as a major global public health challenge. Diverse factors, including climate change, globalization, deforestation, human-animal interactions, lifestyle choices, and various biological factors, can contribute to their emergence and reemergence. Rapid detection and characterization of (re)emerging pathogens are therefore critical for effective outbreak management and for enhancing our understanding of epidemics by monitoring the transmission, spread, evolution, and genomics of pathogens. In this context, next-generation sequencing technologies (NGS), particularly long-read platforms such as Oxford Nanopore Technologies (ONT), have opened new avenues for real-time pathogen monitoring. However, the bioinformatics bottleneck remains a challenge, emphasizing the need for efficient, accessible, and user-friendly analysis tools. RESULTS: Here, we present a tool adapted from the RAMPART software that enables real-time data visualisation of multiplex PCR syndromic panels combined with Oxford Nanopore sequencing. This real-time analysis enables rapid pathogen detection, from raw data acquisition to taxonomic assignment, within minutes. The interface offers dynamic visual tracking of the sequencing run and amplicon coverage, facilitating immediate insights during diagnostic workflows. Validation experiments confirmed the system's reliability, accurately identifying all pathogens present in complex clinical or environmental samples. This tool provides an integrated, user-friendly solution for genomic pathogen surveillance in field or clinical settings.

MOTIVATION: With the continued improvement of requisite mass spectrometers and UHPLC systems, Hydrogen/Deuterium eXchange Mass Spectrometry (HDX-MS) workflows are rapidly evolving towards the investigation of more challenging biological systems, including large protein complexes and membrane proteins. The analysis of such extensive systems results in very large HDX-MS datasets for which specific analysis tools are required to speed up data validation and interpretation. RESULTS: We introduce a web application and a new R-package named 'MEMHDX' to help users analyze, validate and visualize large HDX-MS datasets. MEMHDX is composed of two elements. A statistical tool aids in the validation of the results by applying a mixed-effects model for each peptide, in each experimental condition, and at each time point, taking into account the time dependency of the HDX reaction and number of independent replicates. Two adjusted P-values are generated per peptide, one for the 'Change in dynamics' and one for the 'Magnitude of ΔD', and are used to classify the data by means of a 'Logit' representation. A user-friendly interface developed with Shiny by RStudio facilitates the use of the package. This interactive tool allows the user to easily and rapidly validate, visualize and compare the relative deuterium incorporation on the amino acid sequence and 3D structure, providing both spatial and temporal information. AVAILABILITY AND IMPLEMENTATION: MEMHDX is freely available as a web tool at the project home page http://memhdx.c3bi.pasteur.fr CONTACT: [email protected] or [email protected] information: Supplementary data is available at Bioinformatics online.