Biology subjects

Jaeger-Honz, S.

Publications and source records attributed to Jaeger-Honz, S..

3 recordsLinked to original sources

bioRxiv2025

MeTrEx: Membrane Trajectory Explorer

BackgroundMolecular Dynamics (MD) simulations provide valuable insights into the behaviour of biomolecules, particularly in complex systems such as cellular membranes. However, the increasing volume of MD data presents significant challenges in data visualisation, exploration and analysis. ResultWe present MeTrEx (Membrane Trajectory Explorer), a Python-based software designed to enhance the exploration and analysis of MD simulation data, with a focus on ligand and membrane molecule interactions. MeTrEx offers an intuitive graphical user interface for visualisation, advanced interaction tools, and comprehensive analytical capabilities. The software also supports comparative analyses of molecular trajectories and integrates external datasets for a more holistic view. A case study analysing the interaction of Polymyxin B1 with a bacterial membrane demonstrates the tools capabilities to investigate complex molecular behaviours. ConclusionBy combining detailed molecular analysis with interactive visualisation, MeTrEx provides researchers with a powerful platform to investigate complex biomolecular systems, contributing to a deeper understanding of ligand-membrane interactions.

bioinformatics↗

bioRxiv2024

The (α, β)-k Boolean Signatures of Molecular Toxicity: Microcystin as a Case Study

BackgroundThe (, {beta})-k-Feature Set Problem is a combinatorial problem, that has been proven as alternative to typical methods for reducing the dimensionality of large datasets without compromising the performance of machine learning classifiers. ResultWe present a case study that shows that solutions of the (, {beta})-k-Feature Set Problem help to identify molecular substructures related to toxicity. The dataset investigated in this study is based on the inhibition of ser/thr-proteinphosphatases by Microcystin (MC) congeners. MC congeners are a class of structurally similar cyanobacterial toxins, which are critical to human consumption. ConclusionWe show that it is possible to identify biologically meaningful toxicity signatures by applying the (, {beta})-k feature sets on extended connectivity fingerprint representations of MC congeners. Boolean rules were derived from the feature sets to classify toxicity and can be mapped on the chemical structure, leading to insights on the absence/presence of substructures that can explain toxicity. The presented method can be applied on any other molecular data set and is therefore transferrable to other use cases.

bioinformatics↗

bioRxiv2023

Spatially Resolved Transcriptomics Mining in 3D and Virtual Reality Environments with VR-Omics

The field of spatial transcriptomics is rapidly evolving, with increasing sample complexity, resolution, and tissue size. Yet the field lacks comprehensive solutions for automated integration and analysis of multi-slice data in either stacked (3D) or co-planar (2D) formation. To address this, we developed VR-Omics, a free, platform-agnostic software that distinctively provides end-to-end automated processing of multi-slice data through a biologist-friendly interface. Benchmarking against existing methods demonstrates VR-Omics unique strengths to perform comprehensive end-to-end analysis of multi-slice stacked data. Applied to rare paediatric cardiac rhabdomyomas, VR-Omics uncovered previously undetected dysregulated metabolic networks through co-planar slice analysis, demonstrating its potential for biological discoveries.

bioinformatics↗