bioRxiv

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PPARgene 2.0: leveraging large language models and multi-omics data for enhanced identification and prediction of PPAR target genes

bioRxiv Jan 1, 2025
Peroxisome proliferator-activated receptors (PPARs) are ligand-activated transcription factors of the nuclear receptor superfamily. Upon ligand binding, PPARs activate target gene transcription and regulate a variety of important physiological proces...
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Predictive design of tissue-specific mammalian enhancers that function in vivo in the mouse embryo

bioRxiv Jan 1, 2025
Enhancers control tissue-specific gene expression across metazoans. Although deep learning has enabled enhancer prediction and design in mammalian cell lines and invertebrate systems, it remains unclear whether such approaches can operate within the ...
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Image-based morphological profiling of autophagy phenotypes in Zika virus infected cells

bioRxiv Jan 1, 2025
Autophagy is a dynamic intracellular process that is essential in maintaining cellular homeostasis. Its potential as a therapeutic target is exemplified by its dysregulation in many disease states such as Zika virus (ZIKV) infection. ZIKV poses a sig...
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Mut-BPE: A Modified BPE Strategy Improves Variant Effect Prediction

bioRxiv Jan 1, 2025
Byte Pair Encoding (BPE) is widely used in genome foundation models for its ability to compress long DNA sequences into fewer tokens. However, its variable-length tokens often span multiple nucleotides, limiting the model’s sensitivity to single-nucl...
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Generative AI Enables Breast Cancer Genomic Subtype Prediction from Histology Images

bioRxiv Jan 1, 2025
Breast cancer subtyping is essential for precision oncology, influencing prognosis, treatment selection, and clinical trial design. The Integrative Subtype Classification (IC) categorizes breast tumors into groups with distinct long-term outcomes bas...
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Genetic Influences on Neural Responses in Placebo Analgesia Circuitry

bioRxiv Jan 1, 2025
Placebo analgesia is a well-established medical phenomenon with overlapping neural representations between humans and rodents, but the genetic contribution to this conserved neural circuitry remains unknown. Using functional brain imaging in 305 mono...
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USHER: Guiding Foundation Model Representations through Distribution Shifts

bioRxiv Jan 1, 2025
Foundation models pre-trained on certain biological data modalities exhibit systematic representational biases when encountering out-of-distribution (OOD) data from new assays. The embedding drift largely arises from instrumentation and protocol-rela...
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Islands of Signal and Transcriptomic Sequencing: A Foundation Model for Mutation and Lineage Prediction based on DNA Methylation and RNA-seq

bioRxiv Jan 1, 2025
DNA methylation and RNA-seq provide complementary views of oncogenic state, but their high dimensionality complicates robust modeling. We develop a pancancer, multiomic foundation model that jointly encodes CpG-island DNA methylation and gene express...
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A Reinforcement Learning Approach for Modeling Organic Compound-Induced Antimicrobial Resistance Dynamics

bioRxiv Jan 1, 2025
This study investigates the use of reinforcement learning (RL) to model antimicrobial resistance (AMR) dynamics driven by copper exposure. In a simulated environment, three agent strategies were evaluated: (1) random, (2) rule-based, and (3) Q-learni...
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Cognitive cartography of mammalian brains using meta-analysis of AI experts

bioRxiv Jan 1, 2025
The complexity of the brain is increasingly mirrored by the complexity of the neuroscientific literature, yet no individual mind can fully grasp the diversity of scales, methodologies and model organisms. Where human experts flag, the latest AI model...
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