Biology subjects

Dejean, S.

Publications and source records attributed to Dejean, S..

6 recordsLinked to original sources

bioRxiv2026

BFWalk: backtrack-free network propagation with in-degree normalization

In network medicine, the protein-protein interaction network, or interactome, is an essential resource for identifying candidate proteins underlying diseases and other phenotypic traits. Indeed, it can be leveraged via the guilt-by-association paradigm, which asserts that interacting proteins are likely to participate in the same molecular processes. Network propagation that combines the topology of the interactome with prior knowledge about disease genes is a promising strategy to identify new candidate genes contributing to diseases. However, existing network propagation algorithms are often biased toward highly connected proteins, called "hubs". We present BFWalk, a novel network propagation algorithm designed to avoid inflated scores for hubs. We tested BFWalk across four human phenotypes: multiple morphological abnormalities of the sperm flagella, dyschromatopsia, hypertrophic cardiomyopathy, and chronic kidney disease. For each phenotype, we assessed whether BFWalk could recover known phenotype-associated genes and whether new candidate genes were enriched in relevant tissues. Depending on the phenotype, BFWalk outperformed or matched the state-of-the-art network propagation methods. Furthermore, the results confirmed that BFWalk is free of bias toward high-degree nodes. Therefore, BFWalk is a powerful method for identifying new genes across diverse phenotypes and constitutes a strong alternative to existing network propagation algorithms. Availability: BFWalk is implemented in Python and C. The code is available under the GNU GPL (v3.0) on: https://github.com/jedrzejkubica/BFWalk

bioinformatics↗

bioRxiv2025

Short-term performance prediction in team sports using tracking data.

This research addresses short-term performance prediction in Rugby Union using player tracking data. Rugbys unique characteristics as a conquest sport with strict offside rules make the ball position a crucial performance indicator. We used event data to identify ball carriers in offensive phase and considered their locations as proxy for the ball. We then aim to predict this performance indicator. We formulated this challenge as a time series prediction problem where player positions (multivariate) predict performance (univariate). Our results suggest using player tracking data improves the prediction ability.

animal behavior and cognition↗

bioRxiv2023

3D RNA profile of habenulae in the catshark Scyliorhinus canicula: a reference in jawed vertebrates

We report the generation of a spatially resolved RNA profile of the habenulae in a chondrichthyan, the catshark Scyliorhinus canicula. The digital profiles obtained for candidate markers of the broad territories previously characterized in this species reflect their broad characteristics, including left- or right asymmetric distributions. We use spatial autocorrelation and autocorrelation as measures to analyze these data and identify novel territory markers. These analyses lead to a refined molecular characterization of catshark habenulae and lead to extended lists of markers for the major territories previously identified. They confirm the marked asymmetry of the catshark habenulae, both in its lateral and medial components. In addition, they highlight a bilateral lateral to medial organization in radial bands, which may reflect a temporal regulation of neurogenesis. These data lead to a novel reference to explore the lmode of evolution of habenulae and of their asymmetries across gnathostomes.

developmental biology↗

bioRxiv2020

Integrating independent microbial studies to build predictive models of anaerobic digestion inhibition

Anaerobic digestion (AD) is a microbial process that can efficiently degrade organic waste into renewable energies such as methane-rich biogas. However, the underpinning microbial mechanisms are highly vulnerable to a wide range of inhibitory compounds, leading to process failure and economic losses. High-throughput sequencing technologies enable the identification of microbial indicators of digesters inhibition and can provide new insights into the key phylotypes at stake during AD process. But yet, current studies have used different inocula, substrates, geographical sites and types of reactors, resulting in indicators that are not robust or reproducible across independent studies. In addition, such studies focus on the identification of a single microbial indicator that is not reflective of the complexity of AD. Our study proposes the first analysis of its kind that seeks for a robust signature of microbial indicators of phenol and ammonia inhibitions, whilst leveraging on 4 independent in-house and external AD microbial studies. We applied a recent multivariate integrative method on two-in-house studies to identify such signature, then predicted the inhibitory status of samples from two datasets with more than 90% accuracy. Our study demonstrates how we can efficiently analyze existing studies to extract robust microbial community patterns, predict AD inhibition, and deepen our understanding of AD towards better AD microbial management. HighlightsO_LIRobust biomarkers of AD inhibition were tagged by integrating independent 16S studies C_LIO_LIIncrease of the Clostridiales relative abundance is an early warning of AD inhibition C_LIO_LICloacimonetes is associated with good performance of biomethane production C_LIO_LIMultivariate model predicts ammonia inhibition with 90% accuracy in external data C_LI

microbiology↗

bioRxiv2019

Atrial natriuretic peptide orchestrates a coordinated physiological response to fuel non shivering thermogenesis

Atrial natriuretic peptide (ANP) is a cardiac hormone controlling blood volume and arterial pressure in mammals. It is unclear whether and how ANP controls cold-induced thermogenesis in vivo. Here we show that acute cold exposure induces cardiac ANP secretion in mice and humans. Genetic inactivation of ANP promotes cold intolerance and suppresses about half of cold-induced brown adipose tissue (BAT) activation in mice. While white adipocytes are resistant to ANP-mediated lipolysis at thermoneutral temperature in mice, cold exposure renders white adipocytes fully responsive to ANP to activate lipolysis and a thermogenic program, a physiological response which is dramatically suppressed in ANP null mice. ANP deficiency also blunts liver triglycerides and glycogen metabolism thus impairing fuel availability for BAT thermogenesis. ANP directly increases mitochondrial uncoupling and thermogenic genes expression in human white and brown adipocytes. Together, these results indicate that ANP is a major physiological trigger of BAT thermogenesis upon cold exposure in mammals.

physiology↗

bioRxiv2018

A powerful framework for an integrative study with heterogeneous omics data: from univariate statistics to multi-block analysis

The high-throughput data generated by new biotechnologies used in biological studies require specific and adapted statistical treatments. In this work, we propose a novel and powerful framework to manage and analyse multi-omics heterogeneous data to carry out an integrative analysis. We illustrate it using the package mixOmics for the R software as it specifically addresses data integration issues. Our work also aims at confronting the most recent functionalities of mixOmics to real data sets because, even if multi-block integrative methodologies exist, they still have to be used to enlarge our know-how and to provide an operational framework to biologists. Natural populations of the model plant Arabidopsis thaliana are employed in this work but the framework proposed is not limited to this plant and can be deployed whatever the organisms of interest and the biological question. Four omics data sets (phenomics, metabolomics, cell wall proteomics and transcriptomics) have been collected, analysed and integrated in order to study the cell wall plasticity of plants exposed to sub-optimal temperature growth conditions. The methodologies presented start from basic univariate statistics and lead to multi-block integration analysis, and we highlight the fact that each method is associated to one biological issue. Using this powerful framework led us to novel biological conclusions that could not have been reached using standard statistical approaches.

systems biology↗