AIMC Journal:
bioRxiv

Showing 2261 to 2270 of 4979 articles

Domain-adaptation deep learning models do not outperform simple baseline models in single-cell anti-cancer drug sensitivity prediction

bioRxiv
Tumor drug response is profoundly shaped by cellular heterogeneity, making single-cell resolution essential for precision oncology. While drug-response labels are abundant for cell lines at bulk resolution, translating these predictive models to the ...

Camera trapping and passive acoustic monitoring as non-invasive techniques for the study of small mammals

bioRxiv
Terrestrial small mammals are of significant importance worldwide in providing valuable ecosystem services and acting as invasive species, pests, and carriers of disease. Many species are under threat from anthropogenic stressors and non-invasive tec...

OriGene: A Self-Evolving Virtual Disease Biologist Automating Therapeutic Target Discovery

bioRxiv
Therapeutic target discovery remains a critical yet intuition-driven bottleneck in drug development, typically relying on disease biologists to laboriously integrate diverse biomedical data into testable hypotheses for experimental validation. Here, ...

PMGen: From Peptide-MHC Structure Prediction to Peptide Generation

bioRxiv
Accurate structural modeling of peptide-MHC (pMHC) complexes is a prerequisite for understanding adaptive immunity and developing data-driven immunotherapies. However, current tools are often limited by narrow class coverage, restricted peptide lengt...

High-Resolution Coastal Blue Carbon Site Intelligence: A Multi-Attribute Geospatial Pipeline for National-Scale Mangrove Assessment

bioRxiv
The voluntary blue carbon market is severely bottlenecked by outdated methodologies that apply broad, coast-level carbon averages across low-resolution spatial units, systematically failing to account for micro-site ecological realities and critical ...

ARCH3D: A foundation model for global genome architecture

bioRxiv
Biological foundation models are transforming scientific discovery by creating information-rich representations that enable inference in low-data settings. Progress on these models has mainly been achieved by increasing input contextual information, ...

Spontaneous emergence of topographic organization in a multistream convolutional neural network

bioRxiv
Neurons in the cerebral cortex are organized topographically. In the primate visual cortex, neighboring neurons often respond to similar stimulus parameters, such as receptive field position, orientation, color, and spatial frequency. Preferred stimu...

RNA foundation models enable generalizable endometriosis disease classification and stable gene-level interpretation

bioRxiv
Endometriosis is a chronic inflammatory condition with significant diagnostic delays impacting one in ten reproductive age women worldwide. While machine learning (ML) models trained on transcriptomic data show promise for disease prediction, limited...

Enhancing Detection of Polygenic Adaptation: A Comparative Study of Machine Learning and Statistical Approaches Using Simulated Evolve-and-Resequence Data

bioRxiv
Detecting signals of polygenic adaptation remains a significant challenge in population genomics, as traditional methods often struggle to identify the associated subtle, multi-locus allele-frequency shifts. Here, we introduced and tested several nov...

Plasticity and Language in the Anesthetized Human Hippocampus

bioRxiv
Consciousness is a fundamental component of cognition,1 but the degree to which higher-order pattern recognition relies on it remains disputed.2,3 Here we demonstrate the persistence of oddball discrimination, semantic processing, and online predicti...