121 papers
Systems biology moves beyond studying individual genes or proteins to understand how they work together as a complex, living network. Instead of looking at isolated parts, this field examines the intricate conversations between molecules that drive life, revealing how cellular systems respond to changes and maintain balance. It is a holistic approach that turns vast amounts of data into a coherent story of how organisms function as a whole.
At Gist.Science, we ensure these breakthroughs remain accessible to everyone by processing every new preprint in this category directly from bioRxiv. Our team generates both plain-language explanations for the curious mind and detailed technical summaries for researchers, bridging the gap between rapid scientific discovery and clear understanding.
Below are the latest preprints in systems biology, freshly curated and summarized to help you navigate the cutting edge of network science.
MORPHE is an AI framework that bridges spatial omics and image generation by mapping discrete cell identities and spatial relationships into a continuous latent space, enabling the synthesis, reconstruction, and extension of biologically faithful tissue architectures at single-cell resolution across 2D and 3D datasets.
This study establishes a quantitative, parameter-free framework demonstrating that bacterial competition during starvation is driven by necromass recycling, where physiological differences in maintenance demands and nutrient uptake create frequency-dependent survival dynamics that can be accurately predicted by a shared-energy-pool model.
This paper introduces a unified benchmark demonstrating that single-cell foundation models encode transferable gene regulatory and dynamical priors, with specific components like scGPT's token embeddings and scFoundation's reconstruction head outperforming classical methods in static network reconstruction and dynamic transition probing under zero-shot settings.
This study presents the first signed motif analysis of the *C. elegans* connectome, revealing an overabundance of specific three-node patterns like positive feedforward and negative feedback loops with distinct neuronal layouts, thereby demonstrating the utility of signed motif analysis for understanding biological network organization.
This paper proposes a relaxed, multi-objective optimization algorithm that overcomes the limitations of strict topological alignment to successfully identify large, cohesive conserved regulatory modules across species by accommodating many-to-many orthology mappings in noisy gene regulatory networks.
This study reveals that the structural stability, turnover kinetics, and abundance of proteins in *S. cerevisiae* act as key constraints on protein-protein interaction networks, specifically driving the formation of highly connected hubs through the prevalence of abundant yet unstable proteins while leaving network bottlenecks unaffected.
This paper presents an uncertainty-aware graph representation learning framework that integrates positive-unlabeled classification and ensemble methods to prioritize novel and well-calibrated biomarkers for peripheral artery disease, demonstrating superior predictive performance and biological relevance compared to existing baselines.
Through computer experimentation comparing six kinetic models, this study identifies an electro-binding mechanism for ammonium transport in E. coli that explains energy coupling and reveals how coordinated regulation of the AmtB transporter and glutamine synthetase minimizes futile cycling to ensure robust growth under varying environmental conditions.
The paper introduces Trafikk, a molecular-signalling network-based framework that achieves high predictive accuracy for anticancer drug synergies while providing mechanistic insights into how these synergistic effects emerge across diverse cellular contexts.
This study demonstrates that *Akkermansia muciniphila* alleviates fructose-induced metabolic syndrome by reprogramming the gut microbiota and metabolome to elevate oleoylethanolamide levels, which subsequently activates the gut-hypothalamus axis to improve metabolic health.