q-bio.QM papers | Gist.Science

The intersection of quantum mechanics and biology, known as Q-bio, explores how subtle quantum effects might influence living systems. While often associated with physics, this emerging field investigates whether phenomena like quantum tunneling or entanglement play a role in processes such as photosynthesis, enzyme activity, or even our sense of smell. It challenges the traditional view that life is purely classical, suggesting that the microscopic rules of the quantum world are essential to understanding life itself.

At Gist.Science, we process every new preprint in this category as it appears on arXiv, ensuring you stay at the forefront of this rapidly evolving discipline. We transform these complex studies into accessible plain-language explanations alongside detailed technical summaries, making cutting-edge research available to everyone regardless of their background. Below are the latest papers in Q-bio — Qm, curated and clarified just for you.

🌀 nonlinear sciences

Adaptive High-Level Tight Control of Prostate Cancer: A Path from From Terminal Disease to Chronic Condition

This paper proposes a Stackelberg game-theoretic framework utilizing Bayesian optimization to identify an adaptive high-level tight control (HLTC) chemotherapy strategy for metastatic prostate cancer, demonstrating that precise drug delivery based on closely spaced biomarker triggers can significantly prolong survival and potentially transform the disease from terminal to chronic.

Trung V. Phan, Shengkai Li, Luciana Sarabia, Caroline N. Cappetto, Benjamin Howe, Sarah R. Amend, Kenneth J. Pienta, Joe (…)2026-07-21

🧬 biology

CORE -- A Cell-Level Coarse-to-Fine Image Registration Engine for Multi-stain Image Alignment

The paper introduces CORE, a novel coarse-to-fine framework that achieves accurate, robust, and generalizable nuclei-level registration across diverse multi-stain whole slide images by combining prompt-based tissue filtering, global morphology alignment, and a custom shape-aware point-set registration model for fine-grained non-rigid deformation.

Esha Sadia Nasir, Behnaz Elhaminia, Mark Eastwood, Catherine King, Owen Cain, Lorraine Harper, Paul Moss, Dimitrios Chan (…)2026-07-21

🧬 biology

Preference-based Antibody Expression Ranking: Scaling with Large-scale Weak Supervision

This paper proposes a unified preference-based learning framework that adapts Direct Preference Optimization to integrate scarce quantitative expression data with large-scale weak immunization supervision, enabling protein language models to effectively rank antibody expressibility in data-constrained settings.

Josh Qixuan Sun, Morteza Babaie, Wenyang Hou, Mark Crowley, David Young2026-07-21

🧬 biology

Evaluating multi-season occupancy models with autocorrelation fitted to heterogeneous datasets

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.

André Luís Luza, Didier Alard, Frédéric Barraquand2026-07-20

🧬 biology

A vision foundation model for single-cell biology via spatial gene cartography

The paper introduces scVision, a vision foundation model that transforms single-cell transcriptomes into continuous images by spatially arranging genes based on co-expression, enabling state-of-the-art zero-shot cell-type annotation and gene program recovery without fine-tuning by leveraging the biological signal inherent in gene layout rather than just the neural network architecture.

Ridvan Yesiloglu, Sakib Mostafa, James Zou, Ash Alizadeh, Jiajun Wu, Lei Xing, Ehsan Adeli, Md Tauhidul Islam2026-07-17

🌀 nonlinear sciences

Redefining Fitness: Inference, Information and Phase Transitions in Evolutionary Dynamics

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.

Luís MA Bettencourt, Brandon J Grandison, Jordan T Kemp2026-07-16✓ Author reviewed ⓘ

🧬 biology

RNA-KG v2.0: An RNA-centered Knowledge Graph with Properties

This paper presents RNA-KG v2.0, an enhanced RNA-centered knowledge graph that integrates approximately 100 million manually curated interactions from 91 sources with standardized contextual properties and enriched node attributes to enable advanced context-aware queries and link prediction in RNA research.

Emanuele Cavalleri, Paolo Perlasca, Marco Mesiti2026-07-16

⚡ electrical engineering

Exact Decomposition of Adversarial Dual-Objective Value Functions, with Applications to Optimal Drug Dosing

This paper establishes theoretical conditions under which exact decompositions of adversarial dual-objective value functions remain valid in Hamilton-Jacobi Reachability frameworks and demonstrates their application to solving optimal drug regimen design problems.

Dylan Hirsch, William Sharpless, Sylvia Herbert2026-07-16

🧬 biology

Deciphering the Language of Nature: A transformer-based language model for deleterious mutations in proteins

The paper introduces MutFormer, a transformer-based model that combines self-attention and convolutional layers to predict deleterious missense mutations in human proteins, demonstrating performance comparable to or better than existing tools by effectively capturing both short-range and long-range sequence dependencies.

Theodore Jiang, Li Fang, Kai Wang2026-07-15✓ Author reviewed ⓘ

🧬 biology

Blini: lightweight nucleotide sequence search and dereplication

Blini is a lightweight, efficient tool designed to rapidly search nucleotide sequences and dereplicate large collections of contigs or long sequences, offering superior speed and lower memory usage compared to existing solutions while maintaining high accuracy.

Amit Lavon2026-07-15