Biology subjects

Samson, F.

Publications and source records attributed to Samson, F..

3 recordsLinked to original sources

bioRxiv2026

The Q1K Integrated EEG and Eye-Tracking Experimental Test Battery for Open Autism Science

The Quebec 1000 Families (Q1K) platform has been designed to recruit, phenotype, and collect biospecimens from a large cohort of families with at least one member with autism spectrum disorder or a related neurodevelopmental condition. As part of the Q1K protocol, an experimental test battery was developed and validated using simultaneous high-density electroencephalography (EEG) and eye tracking (ET). We report on the general approach and design principles, multimodal EEG/ET integration, the tasks, and their validation, providing a blueprint for implement such a project. It also describes the cohort and its methods as a reference for future studies using this dataset. By releasing openly this experimental test battery, we aim to support task standardization and multi-project data pooling in autism and related neurodevelopmental disorders.

neuroscience↗

bioRxiv2022

Plant-PLMview: a database for identifying cis-regulatory sequences with preferential positions in gene-proximal regions of plants

BackgroundEstablishing relationships between transcription factors and target genes is essential for understanding the mechanisms regulating gene expression, which play a fundamental role in plant adaptation to the local environment. Despite the importance of this research area and the tremendous progress in sequencing methods such as ChIP-seq and DAP-seq, we are still far from a complete reconstruction of the cis-regulatory landscape. Only a small number of transcription factors can be assessed from experimental data to identify their cis-regulatory binding sites. This highlights the role that in silico approaches can play to complement experimental data. ResultsWe have developed Plant-PLMview, a web-accessible database for detecting preferentially cis-regulatory sequences in the gene-proximal regions of 20 plant species. Users of Plant-PLMview can (i) access the proximal regions of controlled genes from 20 plant species, (ii) query their own DNA motifs or access 840 cis-regulatory sequences from various plant resources, and (iii) use a tool called PLMdetect to search for preferentially located motifs in the gene-proximal regions of a list of genes. Results are displayed via a web interface with a list of DNA motifs preferentially located in a region near the start or end of genes, the distribution of these motifs and associated annotations. In addition, a graphical map of the preferential locations of the motifs in the 5 and 3-proximal regions of genes provides an overview of all motifs and genes examined. ConclusionPlant-PLMview provides the opportunity to study the proximal landscape of gene regulation in 20 plant genomes. The originality of the database lies in its ease of use thanks to the curated data (cis-regulatory sequences and proximal regions of genes) and the possibility to search through PLMdetect in the 5-gene-proximal region, but also in the 3-gene-proximal region, which is rarely explored. The web interface provides numerous graphical views that allow the users to get an overview and interpret the results more easily.

bioinformatics↗

bioRxiv2020

The first AI-based mobile application for antibiotic resistance testing

Antimicrobial resistance is a major global health threat and its development is promoted by antibiotic misuse. While disk diffusion antibiotic susceptibility testing (AST, also called antibiogram) is broadly used to test for antibiotic resistance in bacterial infections, it faces strong criticism because of inter-operator variability and the complexity of interpretative reading. Automatic reading systems address these issues, but are not always adapted or available to resource-limited settings. We present the first artificial intelligence (AI)-based, offline smartphone application for antibiogram analysis. The application captures images with the phones camera, and the user is guided throughout the analysis on the same device by a user-friendly graphical interface. An embedded expert system validates the coherence of the antibiogram data and provides interpreted results. The fully automatic measurement procedure of our applications reading system achieves an overall agreement of 90% on susceptibility categorization against a hospital-standard automatic system and 98% against manual measurement (gold standard), with reduced inter-operator variability. The applications performance showed that the automatic reading of antibiotic resistance testing is entirely feasible on a smartphone. Moreover our application is suited for resource-limited settings, and therefore has the potential to significantly increase patients access to AST worldwide.

microbiology↗