bioRxiv

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Empirical Evaluation of Single-Cell Foundation Models for Predicting Cancer Outcomes

bioRxiv Jan 1, 2025
Foundation models pretrained on large-scale single-cell RNA sequencing data present a promising opportunity to advance translational cancer research. However, their utility in clinically relevant, patient-level applications of single-cell analysis re...
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Multilingual Computational Models Capture a Shared Meaning Component in Brain Responses across 21 Languages

bioRxiv Jan 1, 2025
At the heart of language neuroscience lies a fundamental question: How does the brain process the rich variety of languages? Multilingual neural network models offer a way to answer this question by representing linguistic content across languages in...
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A generalizable cross-continent prediction of esophageal squamous cell carcinoma using the oral microbiome

bioRxiv Jan 1, 2025
Esophageal squamous cell carcinoma (ESCC) is a disease with limited tools for early screening and a poor prognosis. Symptoms typically appear late, and early cancer is hard to detect without endoscopic screening, which is inaccessible in most high-ri...
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Uncertainty-Aware Deep Learning for Multi-Metric and Dose-Specific Prediction of Drug Synergy

bioRxiv Jan 1, 2025
Accurately predicting drug synergy is critical to accelerate the development of combination therapies for cancer and other complex diseases. Yet, the vast combinatorial drug and dose space poses a substantial challenge, even for modern deep learning ...
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Lower engagement of cognitive control, attention, modulation networks and lower creativity in children while using ChatGPT: an fMRI study

bioRxiv Jan 1, 2025
Generative AI can scaffold idea generation, but how it engages control, attention, and memory systems in the developing versus mature brain, and how this relates to creativity, remains unclear. We compared 6-7-year-old (N = 15) children and adults (N...
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Data-Driven Symbolic Higher-Order Epistasis Discovery with Kolmogorov-Arnold Networks

bioRxiv Jan 1, 2025
Many human diseases are polygenic conditions that arise from a complex interplay of interactions between multiple genes at different loci, but currently most Genome-Wide Association Studies (GWAS) largely only consider the main additive effects of si...
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Predictive learning enables compositional representations

bioRxiv Jan 1, 2025
The brain builds predictive models to plan future actions. These models generalize remarkably well to new environments, but it is unclear how neural circuits acquire this flexibility. Compositional representations, which have been observed in the bra...
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CIRPIN: Learning Circular Permutation-Invariant Representations to Uncover Putative Protein Homologs

bioRxiv Jan 1, 2025
Protein structure-based homology detection has been revolutionized by deep learning methods that can rapidly search massive databases. However, current structural search tools often miss proteins related by topological rearrangements, particularly ci...
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Decode-gLM: Tools to Interpret, Audit, and Steer Genomic Language Models

bioRxiv Jan 1, 2025
While genomic language models are enabling the de novo design of entire genomes, they remain challenging to interpret, limiting their trustworthiness. Here, we show that sparse autoencoders (SAEs) trained on Nucleotide Transformer activations decompo...
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Representational drift shows same-class acceleration in visual cortex and artificial neural networks

bioRxiv Jan 1, 2025
The neural code is not fixed but shows substantial representational drift over time. It has been proposed that representational drift reflects continuous learning resulting from input-dependent plasticity. Using theoretical analysis and simulations i...
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