314 papers
Q-Bio — Pe explores the fascinating intersection where physics meets living systems, using mathematical models to decode how biological structures behave and evolve. This field applies rigorous physical principles to understand everything from protein folding to cellular mechanics, offering a quantitative lens on life's most complex processes.
At Gist.Science, we continuously process every new preprint in this category directly from arXiv to make these groundbreaking findings accessible to everyone. For each paper, we provide both a clear, plain-language overview for general readers and a detailed technical summary for specialists, ensuring no insight is lost in translation.
Below are the latest papers in this dynamic field, freshly summarized to help you navigate the cutting edge of physical biology.
This paper derives exact moments and strong laws of large numbers for the driver site frequency spectrum in a supercritical two-type birth-death process with mutation and selection, establishing a cutoff frequency for clone sizes and providing a framework for estimating evolutionary parameters in exponentially growing populations.
This paper proposes a theoretical framework and a minimal model to explain the phenomenon of transient bimodality in dynamical systems, deriving a general criterion for its occurrence and demonstrating that both slow-to-fast and fast-to-slow dynamics can drive this noise-induced behavior with significant implications for cell differentiation and speciation.
This paper presents a non-smooth ordinary differential equation model of dengue transmission that integrates finite hospital capacity and threshold-triggered fogging interventions, revealing how these state-dependent constraints and control policies generate complex dynamics like oscillatory outbreaks and bifurcations to guide the design of effective, resource-aware intervention strategies.
This study evaluates multi-season occupancy models with autocorrelation on heterogeneous datasets, finding that while they are robust to covariate overlap and uneven survey frequencies, they suffer from identifiability issues and produce biased predictions when spatiotemporal data gaps are present.
This paper proposes a deterministic, steady-state-independent model that leverages the observed stability of age-dependent case distributions across varying outbreak intensities in Brazil to estimate the efficacy of interventions, such as dengue vaccines, and determine optimal vaccination strategies.
This paper defines and characterizes classes of unrooted phylogenetic networks that remain valid or retain specific structural properties regardless of root placement, establishing that robust orientability requires the absence of sink components while robustly maintaining properties like being tree-child, stack-free, or normal imposes increasingly strict constraints, ultimately reducing to level-1 or tree structures.
This paper proposes a distinction between syntactic and semantic complexity to argue that evolutionary paths toward optimal fitness are path-dependent, resulting in either a driven mode where both complexities rise together or an entropic mode where syntactic complexity drifts upward under near-neutral conditions, ultimately determining whether lineages achieve high fitness with minimal or excessive structural elaboration.
This paper resolves contradictions in previous simulation studies regarding the "trembling hand hypothesis" by theoretically analyzing the Hawk-Dove game with timescale separation, demonstrating that stochastic demographic noise in finite populations can drive the emergence and persistence of polymorphic states.
This paper introduces a novel infectious disease model that integrates the concept of exposure as a distinct state separate from infection and utilizes a discrete age-of-infection structure to link viral load with the probability of transmission.
This paper resolves fundamental issues in evolutionary theory by redefining fitness as a Bayesian likelihood, demonstrating that natural selection acts to maximize the mutual information between population structure and environmental statistics, thereby establishing information maximization as the governing principle of evolution.