96 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.
This paper introduces UQ-PhysiCell, an open-source, extensible Python framework that streamlines uncertainty quantification, calibration, and model selection for PhysiCell agent-based models by providing a scalable, parallelized workflow that integrates with established statistical analysis libraries.
This study demonstrates that integrating proteomic kinome profiling with machine learning enables the prediction of kinase inhibitor cardiotoxicity by identifying specific off-target kinase engagements, such as PDGFRB and EGFR, that drive adverse cardiac events.
This study integrates multi-cohort transcriptomics and network pharmacology to identify CD44 as a key hub gene in PCOS granulosa cells and prioritizes specific gene-drug pairs, such as GJA5 with flufenamic acid, as promising candidates for future therapeutic development.
This study utilizes whole blood transcriptome analysis of pigs to characterize the distinct temporal dynamics of heat acclimation, revealing a biphasic response where short-term adaptation is driven by immune activation and heat shock proteins, while long-term acclimation involves complex metabolic shifts in lipid metabolism and oxidative phosphorylation to restore homeothermy.
This study establishes a resource competition model that disentangles the fitness cost of gene expression into distinct components driven by ribosome, RNA polymerase, and transcription factor limitations, revealing that these costs originate from the transcription and translation processes themselves rather than the gene products, thereby providing a quantitative framework to optimize genetic design in synthetic biology.
This study extends a computational model of quadrupedal locomotion to demonstrate that animals utilize distinct, speed-dependent asymmetrical turning strategies—specifically body bending at low speeds, lateral force application at medium speeds, and lateral limb shifting at high speeds—with forelimbs primarily driving steering while hindlimbs modulate propulsion and stability.
HiMaLAYAS is a Python-based framework that enables post hoc enrichment-based annotation of hierarchically clustered matrices by treating clusters as statistical units to test and visualize significant annotations across both biological and non-biological domains.
This study employs an integrative MultiOmics approach on harbour porpoises with compromised respiratory health to reveal systemic molecular signatures of immune and metabolic dysregulation across lung and muscle tissues, offering novel biomarkers for monitoring anthropogenic impacts on marine species.
This study systematically demonstrates that differentiating human iPSCs into cardiomyocytes via distinct protocols yields biologically unique cell states with varying disease-relevance, establishing a framework to match specific differentiation strategies with genetic architectures of cardiovascular diseases for optimized disease modelling.
This paper demonstrates that a bistable metabolic switch in *Saccharomyces cerevisiae*, which determines whether cells adopt a fermenting "arrestor" or respiring "recoverer" state, arises from the competition between mitochondrial and cytosolic ribosomes, where the relative rates of mitochondrial versus cytoplasmic protein synthesis govern the positive feedback loop required for this conserved epigenetic transition.