q-bio.QM papers | Gist.Science

Domain-aware priors stabilize, not merely enable, vertical federated learning in data-scarce coral multi-omics

This paper demonstrates that incorporating domain-aware priors, specifically gradient saliency-guided feature selection with biological constraints, significantly stabilizes vertical federated learning for coral multi-omics classification under extreme data scarcity (P >> N), enabling the REEF framework to substantially outperform generic and state-of-the-art baselines while reducing variance and ensuring interpretability.

Sam VictorWed, 11 Ma🧬 q-bio

Understanding the temperature response of biological systems: Part I -- Phenomenological descriptions and microscopic models

This review article surveys phenomenological and microscopic models used to describe the complex, non-Arrhenius temperature responses of biological systems across various scales, defining key operational metrics like optimal temperatures and thermal limits while setting the stage for a subsequent discussion on how system-level curves emerge from interacting reactions.

Simen Jacobs, Julian Voits, Nikita Frolov, Ulrich S. Schwarz, Lendert GelensWed, 11 Ma🧬 q-bio

Integrating Mechanistic Modeling and Machine Learning to Study CD4+/CD8+ CAR-T Cell Dynamics with Tumor Antigen Regulation

This paper presents an extended mechanistic model of CD4+/CD8+ CAR-T cell dynamics regulated by tumor antigen burden, demonstrating how combining sensitivity analysis with machine learning can elucidate treatment drivers and partially recover predictive accuracy from noisy patient data despite parameter uncertainty.

Saranya Varakunan, Melissa Stadt, Mohammad KohandelWed, 11 Ma🧬 q-bio

Association of Radiologic PPFE Change with Mortality in Lung Cancer Screening Cohorts

This study demonstrates that the longitudinal progression of radiologic pleuroparenchymal fibroelastosis (PPFE), quantified via automated analysis of low-dose CT scans, independently predicts increased mortality and adverse respiratory outcomes in large lung cancer screening cohorts.

Shahab Aslani, Mehran Azimbagirad, Daryl Cheng, Daisuke Yamada, Ryoko Egashira, Adam Szmul, Justine Chan-Fook, Robert Chapman, Alfred Chung Pui So, Shanshan Wang, John McCabe, Tianqi Yang, Jose M Brenes, Eyjolfur Gudmundsson, The SUMMIT Consortium, Susan M. Astley, Daniel C. Alexander, Sam M. Janes, Joseph JacobWed, 11 Ma🧬 q-bio

Sequential learning theory for Markov genealogy processes

This paper introduces a filtration-based sequential learning framework that decomposes the impact of adding taxa on phylodynamic inference into learning, mismatch, and covariance components, revealing fundamental limits on what sequence data alone can reveal about latent genealogies due to irreducible gaps between analyst and oracle performance.

David J PascallWed, 11 Ma🧬 q-bio

Exploring Strategies for Personalized Radiation Therapy Part IV: An Interaction-Picture Approach to Quantifying the Abscopal Effect

This paper introduces a quantum mechanics-inspired interaction-picture framework to quantify the abscopal effect as a continuous, stochastic phenomenon in the context of PULSAR, enabling individual-level analysis of tumor interactions and standardized cross-study comparisons in preclinical models.

Hao Peng, Laurentiu Pop, Kai Jiang, Faya Zhang, Debabrata Saha, Raquibul Hannan, Robert TimmermanWed, 11 Ma🧬 q-bio

CryoNet.Refine: A One-step Diffusion Model for Rapid Refinement of Structural Models with Cryo-EM Density Map Restraints

CryoNet.Refine is a novel one-step diffusion model that automates and accelerates the refinement of atomic structures against cryo-EM density maps, outperforming traditional tools like Phenix in both model-map correlation and geometric quality while supporting diverse protein and nucleic acid complexes.

Fuyao Huang, Xiaozhu Yu, Kui Xu, Qiangfeng Cliff ZhangTue, 10 Ma💻 cs

RadDiff: Retrieval-Augmented Denoising Diffusion for Protein Inverse Folding

This paper introduces RadDiff, a novel retrieval-augmented denoising diffusion model that effectively integrates up-to-date protein knowledge into the inverse folding process, significantly outperforming existing methods in sequence recovery rate and foldability while offering greater parameter efficiency and scalability.

Jin Han, Tianfan Fu, Wu-Jun LiTue, 10 Ma💻 cs

HarmonyCell: Automating Single-Cell Perturbation Modeling under Semantic and Distribution Shifts

HarmonyCell is an end-to-end agent framework that automates single-cell perturbation modeling by combining an LLM-driven semantic unifier to resolve metadata incompatibilities and an adaptive Monte Carlo Tree Search engine to synthesize architectures that handle distribution shifts, thereby achieving high execution success and outperforming expert baselines without manual engineering.

Wenxuan Huang, Mingyu Tsoi, Yanhao Huang, Xinjie Mao, Xue Xia, Hao Wu, Jiaqi Wei, Yuejin Yang, Lang Yu, Cheng Tan, Xiang Zhang, Zhangyang Gao, Siqi SunTue, 10 Ma💻 cs

ViroGym: Realistic Large-Scale Benchmarks for Evaluating Viral Proteins

The paper introduces ViroGym, a comprehensive benchmark comprising extensive deep mutational scanning data and real-world tasks to evaluate protein language models for predicting viral variant effects and guiding rational antigen selection for vaccine development.

Yichen Zhou, Jonathan Golob, Amir Karimi, Stefan Bauer, Patrick SchwabTue, 10 Ma💻 cs

When Many Trees Go to War: On Sets of Phylogenetic Trees With Almost No Common Structure

This paper establishes that for a set of $t$ phylogenetic trees with $n$ leaves, if $t$ is sufficiently small (specifically $t \in o(\sqrt{\lg n})$ ), the trees can be constructed to have virtually no common structure, thereby forcing any network displaying them to require nearly the maximum possible number of reticulations, $(t-1)n - o(n)$ .

Mathias Weller, Norbert ZehTue, 10 Ma🔢 math

Minority-Triggered Reorientations Yield Macroscopic Cascades and Enhanced Responsiveness in Swarms

The paper proposes a biologically plausible mechanism where agents occasionally follow a deviating minority neighbor rather than the majority, a simple rule that triggers heavy-tailed reorientation cascades and significantly enhances a swarm's responsiveness to environmental changes while maintaining group cohesion.

Simon Syga, Chandraniva Guha Ray, Josué Manik Nava-Sedeño, Fernando Peruani, Andreas DeutschTue, 10 Ma🔬 physics

Hydrodynamic origins of symmetric swimming strategies

This paper demonstrates that spatial symmetry acts as a fundamental physical optimality principle for efficient locomotion in viscous fluids, explaining the prevalence of symmetric swimming gaits in nature through a hydrodynamic duality that proves symmetric strokes yield optimal speeds and efficiencies unattainable by generic non-symmetric strokes.

Takahiro Kanazawa, Kenta Ishimoto, Kyogo KawaguchiTue, 10 Ma🔬 physics

Double projection for reconstructing dynamical systems: between stochastic and deterministic regimes

This paper introduces a "double projection" method within dynamical variational autoencoders that simultaneously estimates system state trajectories and noise time series from data, enabling effective multi-step reconstruction and learning of low-dimensional stochastic models across various benchmark problems.

Viktor Sip, Martin Breyton, Spase Petkoski, Viktor JirsaTue, 10 Ma🤖 cs.LG

Distilling and Adapting: A Topology-Aware Framework for Zero-Shot Interaction Prediction in Multiplex Biological Networks

This paper proposes a novel topology-aware framework that leverages domain-specific foundation models, a graph tokenizer for multiplex connectivity, and knowledge distillation to achieve robust zero-shot interaction prediction in multiplex biological networks, outperforming state-of-the-art methods.

Alana Deng, Sugitha Janarthanan, Yan Sun, Zihao Jing, Pingzhao HuTue, 10 Ma🤖 cs.LG

Optical Manipulation of Erythrocytes via Evanescent Waves: Assessing Glucose-Induced Mobility Variations

This study demonstrates that evanescent wave-based optical manipulation can non-invasively detect significant glucose-induced reductions in red blood cell mobility, suggesting its potential as a tool for probing membrane mechanical properties.

T. Troncoso Enríquez, J. Staforelli-Vivanco, I. Bordeu, M. González-OrtizTue, 10 Ma🔬 physics.optics

Three-Dimensional Volumetric Reconstruction of Native Chilean Pollen via Lens-Free Digital In-line Holographic Microscopy

This study demonstrates a robust, label-free methodology using lens-free digital in-line holographic microscopy to achieve high-resolution 3D volumetric reconstruction and precise morphological characterization of native Chilean pollen grains, offering a scalable solution for automated melissopalynology and biodiversity assessment.

J. Staforelli-Vivanco, V. Salamanca-Levi, R. Jofré-Cerda, M. Rondanelli-Reyes, I. LamasTue, 10 Ma🔬 physics.optics

Alignment conditions of the human eye for few-photon vision experiments

This study utilizes a 3D eye model and ray tracing simulations to determine that optimal few-photon vision experiments require stimuli to be presented at an inferior angle of 12.6 degrees relative to the visual axis, with alignment precision better than 0.90 degrees to ensure stimuli reach the retina's most sensitive region.

T. H. A. van der Reep, W. LöfflerThu, 12 Ma🔬 physics.optics

pHapCompass: Probabilistic Assembly and Uncertainty Quantification of Polyploid Haplotype Phase

The paper introduces pHapCompass, a probabilistic algorithm for assembling and quantifying uncertainty in polyploid haplotypes that addresses read assignment ambiguity through graph-theoretic inference, while also providing a realistic simulation workflow and generalized evaluation metrics to demonstrate its competitive performance against existing assemblers.

Marjan Hosseini (School of Computing, University of Connecticut), Ella Veiner (School of Computing, University of Connecticut), Thomas Bergendahl (School of Computing, University of Connecticut), Tala Yasenpoor (School of Computing, University of Connecticut), Zane Smith (Department of Entomology and Plant Pathology, University of Tennessee), Margaret Staton (Department of Entomology and Plant Pathology, University of Tennessee), Derek Aguiar (School of Computing, University of Connecticut, Institute for Systems Genomics, University of Connecticut)Thu, 12 Ma🧬 q-bio

Multi-factor modeling of chlorophyll-a in South China's subtropical reservoirs using long-term monitoring data for quantitative analysis

This study utilizes long-term monitoring data from three Guangdong reservoirs to develop a dynamic multi-factor hydro-ecological model that reveals total nitrogen as a more influential driver than total phosphorus for chlorophyll-a proliferation and quantifies the synergistic enhancement of algal growth when water temperatures exceed 25°C alongside high nitrogen levels.

Haizhao Guan, Yiyuan Niu, Chuanjin Zu, Ju KangThu, 12 Ma🧬 q-bio