Biology subjects

Ley, M.

Publications and source records attributed to Ley, M..

5 recordsLinked to original sources

bioRxiv2026

Graph Lens Lite: An interactive biological network viewer for displaying, exploring, and sharing disease pathobiology and drug mechanism of action models

Biological network visualization together with graph-based analyses are key techniques in systems biology and network medicine to detect patterns and generate hypotheses regarding disease pathobiology, drug target identification, biomarker prioritization, and digital drug discovery. Network representations provide an intuitive way to communicate and share research findings. We have developed Graph Lens Lite, a browser-based tool that combines rich visualization with a streamlined interface for exploring and sharing biological networks. It offers an expressive query language, topological network analysis, interactive filtering, visual grouping, customizable layouts, a data editor, fine-grained property-based styling, animated edge-flow visualization, community detection, and a context-aware locally powered AI assistant particularly suited for exploring molecular models of disease pathobiology or drug mechanism of action. We demonstrate its utility on a curated network model of autosomal dominant polycystic kidney disease. Graph Lens Lite is open source, with a live web version available at https://delta4ai.github.io/GraphLensLite/.

bioinformatics↗

bioRxiv2026

systematic evaluation and benchmarking of text summarization methods for biomedical literature: From word-frequency methods to language models

The rapid expansion of biomedical literature demands automated summarization tools that reliably condense research articles into concise, accurate summaries. We benchmarked 62 summarization methods, ranging from frequency-based and TextRank extractors to encoder-decoder models (EDMs) and large language models (LLMs), on 1,000 biomedical abstracts from 20 journals across ScienceDirect and Cell Press, using author-written highlights as reference summaries. Models were evaluated with a composite suite of lexical, semantic, and factual metrics, including ROUGE, BLEU, METEOR, embedding-based similarity, and factuality scores. General-purpose models (e.g., Mistral, GPT, Llama) achieved the highest overall performance across lexical and semantic dimensions, outperforming reasoning-oriented (e.g., DeepSeek, Magistral) and domain-specific (e.g., BioGPT, BioMistral) models. Notably, medium-sized models outperformed large-scale models, suggesting an optimal balance between model capacity and efficiency, while classical extractive methods lagged behind neural approaches. These findings provide a systematic reference for selecting biomedical summarization tools and highlight that broad pretraining outperforms narrow domain adaptation.

bioinformatics↗

bioRxiv2025

R2TP-like Quaternary Chaperones: a comprehensive overview to understand the dynamic R2SP complex

The human R2SP complex belongs to the R2TP-like quaternary chaperone family and consists of RUVBL1, RUVBL2, SPAG1 and PIH1D2. R2SP is crucial for the correct assembly of motile cilia (SPAG1 null mutations cause Primary Ciliary Dyskinesia) and the organization of the synaptic zone. RUVBL1/2 ATPases are the powerhouse of this molecular machinery, while SPAG1 and PIH1D2 would be adaptors that interact with specific clients to promote their quaternary assembly. Despite these functional data, little is known about the structure of R2SP and the precise mode of action of these R2TP-like complexes. We have combined biochemical and structural approaches (NMR, structural mass spectrometry and cryo-EM) to investigate the 3D organization of the human R2SP complex, its mode of assembly and ATPase activity. Our study reveals a three-dimensional structure similar to that of the canonical R2TP complex, but also highlights differences in the mode of action of its RUVBL1/2 ATPase core as well as the binding of its adaptors SPAG1 and PIH1D2.

biophysics↗

bioRxiv2019

PPARG is a tumor suppressor in basal bladder tumors offering new potential therapeutic opportunities.

PPAR{gamma} activation is a critical event in luminal muscle-invasive bladder cancer (MIBC) tumorigenesis, favoring both tumor cell growth and microenvironment modulation toward tumor immune escape. Conversely, the down-regulation of PPAR{gamma} activity in basal MIBC suggests tumor suppressive effects in this subgroup. Here, we report genetic, epigenetic and functional evidence to support the tumor suppressor role for PPAR{gamma} in basal bladder tumors. We identified hemizygous deletions, DNA hyper-methylation and loss-of-function mutations of PPAR{gamma} in basal MIBC, associated with PPAR{gamma} under-expression and its decreased activity. Re-expression of PPAR{gamma} in basal tumor cells resulted in the activation of PPAR{gamma} -dependent transcription program that modulated fatty acid metabolism and cell differentiation and decreased cell growth, which could partly rely on EGFR down-regulation. Structure-function studies of two PPAR{gamma} mutant revealed a destabilization of a region important for coactivator recruitment and should help develop potent molecules to activate PPAR{gamma} as a therapeutic strategy for basal MIBC. The identification of this subtype-dependent dual role of PPAR{gamma} in MIBC strengthens the critical role of PPAR{gamma} in bladder tumorigenesis and reinforces the interest in stratified medicine based on tumor molecular subtyping. One sentence summaryGenetic, epigenetic and functional evidence of a tumor suppressor role for PPAR{gamma} in basal bladder tumors offer new therapeutic opportunities for this subgroup.

cancer biology↗

bioRxiv2016

Degenerate time-dependent network dynamics anticipate seizures in human epileptic brain

Epileptic seizures are known to follow specific changes in brain dynamics. While some algorithms can nowadays robustly detect these changes, a clear understanding of the mechanism by which these alterations occur and generate seizures is still lacking. Here, we provide cross-validated evidence that such changes are initiated by an alteration of physiological network state dynamics. Specifically, our analysis of long intracranial EEG recordings from a group of 10 patients identifies a critical phase of a few hours in which time-dependent network states become less variable (\"degenerate\") and is followed by a global functional connectivity reduction before seizure onset. This critical phase is characterized by an abnormal occurrence of highly correlated network instances and is shown to particularly affect the activity of resection regions in patients with validated postsurgical outcome. Our approach characterizes pre-seizure networks dynamics as a cascade of two sequential events providing new insights into seizure prediction and control.

neuroscience↗