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32 curated papers across all published weeks — sorted by disruptiveness score.
Many biological discovery problems require experiments to be selected sequentially under constrained budgets. CRISPR screening is a prominent example, as exhau…
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2026-W38
This study aims to explore the applicability of Transformer-based models for genetic sequence classification by evaluating their performance in predicting hepa…
2026-W36
The reproducibility of organ morphology and the extent to which computational models can predict morphogenesis remain difficult to quantify, particularly for o…
2026-W40
We introduce a family of prime-base hybrid editors that correct multiple pathogenic SNVs in parallel with reduced double-strand break toxicity, demonstrated in…
2026-W30
Existing cell embedding methods predominantly rely on transcriptomic or proteomic measurements and represent each cell as a holistic entity, thereby overlookin…
2026-W37
We design modular protein logic circuits that perform multi-input cellular computations in mammalian cells, enabling sense-and-respond therapeutic programs wit…
Lung cancer screening with low-dose chest computed tomography reduces mortality, but its impact is limited by uptake, adherence, and management challenges. Blo…
Alzheimer's disease (AD) progresses as a continuous biological process, whereas most existing neuroimaging-based artificial intelligence methods remain limited…
2026-W35
Segmentation of curvilinear anatomical structures in 3D medical images remains challenging due to complex topology, severe class imbalance, weak contrast, and…
We train neural cellular automata to design biocompatible scaffold growth programs that regenerate complex tissue geometries in silico and guide 3D bioprinting…
Predicting transcriptional responses to specific perturbations is critical for understanding cellular regulatory mechanisms and accelerating drug discovery. Si…
Peptides occupy a particularly challenging regime of biomolecular dynamics. Short peptides lack a stable folded core and populate broad conformational ensemble…
2026-W41
Cardiac T1 and T2 quantitative magnetic resonance imaging (MRI) is a technique that provides characterization of a multitude of myocardial pathologies. However…
2026-W39
Multiparameter flow cytometry generates high-dimensional, unordered single-cell mea- surement data for disease diagnosis and monitoring, yet analysis often rem…
Protein generative models have shown remarkable promise in protein design, yet their success rates remain constrained by reliance on curated sequence-structure…
2026-W34
Histology images contain rich morphological information and can provide insights into pathological processes. However, deriving hypotheses relating morphologic…
Single-particle cryo-electron microscopy (cryo-EM) has become a widely adopted technique for biomolecular structure determination. The conventional cryo-EM com…
Bioinformatics workflows rely heavily on visual representations. Quality-control plots, cell embeddings, heatmaps, genome-browser tracks, and interactive dashb…
Bioassay activity prediction is often data-limited because drug-discovery datasets rely on time-consuming and expensive wet-lab experiments for data generation…
Tokenization is a central design choice in genomic language models, yet most deoxyribonucleic acid (DNA) tokenizers use characters, fixed-length k-mers, or fre…
Biological systems often synchronize their dynamics with periodic environmental and intracellular signals. Whether such periodic coordination can also improve…
2026-W31
Identifying therapeutic target genes from single-cell RNA sequencing (scRNA-seq) data remains a fundamental challenge in translational biology. Unlike bulk ass…
Parkinson's disease is clinically and biologically heterogeneous, yet its spatiotemporal progression remains poorly characterized. We present a connectome-cons…
Network control theory applied to structural connectomes typically ranks brain regions as candidate driver nodes by their structural connectivity strength, and…
2026-W32
Proteins occupy heterogeneous free-energy landscapes in which high-entropy ensembles converge toward compact, low-energy basins with multiple sub-states. Molec…
We study a self-supervised generation task for single-cell gene expression vectors: given a set of vectors from a cell type, we aim to generate additional gene…
Epitopes determine where antibodies bind antigens and shape downstream therapeutic properties such as functional blockade and escape resistance, making epitope…
Respiration provides a continuously available window into physiological state and behavior. However, monitoring it outside controlled settings remains challeng…
In bioreactor experiments, budding yeast can manifest stable metabolic oscillations. In some instances these oscillations involve the cell cycle and are associ…
Survival analysis is an established framework for analyzing time-to-event data, yet many clinical machine learning studies still binarize the outcome before mo…
Deep learning models can predict cancer recurrence from H&E stained slides, but the localized molecular states underlying these predictions remain largely…
Chemical kinetics has long inferred local molecular behaviour through the flask-and-molarity pairing, where well-mixed concentrations serve as the experimental…
