AIMC Journal:
bioRxiv

Showing 2541 to 2550 of 4979 articles

GAISHI: A Python Package for Detecting Ghost Introgression with Machine Learning

bioRxiv Feb 3, 2026
Summary: Ghost introgression is a challenging problem in population genetics. Recent studies have explored supervised learning models, namely logistic regression and UNet++, to detect genomic footprints of ghost introgression. However, their applicab...
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Organellomics: AI-driven deep organellar phenotyping reveals novel ALS mechanisms in human neurons

bioRxiv Feb 2, 2026
Systematic assessment of organelle architectures, termed the organellome, offers valuable insights into cellular states and pathomechanisms, but remains largely uncharted. Here, we present a deep phenotypic learning based on vision transformers, resu...
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MLMarker: A machine learning framework for tissue inference and biomarker discovery

bioRxiv Feb 2, 2026
MLMarker is a machine learning tool that computes continuous tissue similarity scores for proteomics data, addressing the challenge of interpreting complex or sparse datasets. Trained on 34 healthy tissues, its Random Forest model generates probabili...
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TwinCell: Large Causal Cell Model for Reliable and Interpretable Therapeutic Target Prioritisation

bioRxiv Feb 2, 2026
Drug discovery is impeded by the difficulty of translating targets from preclinical models to patients. Here, we present TwinCell, a Large Causal Cell Model (LCCM) capable of generalising from in vitro cell lines to patient-derived cell types while p...
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BlueNuclei: automated identification and classification of live and dead transfected neurons using interpretable features

bioRxiv Feb 2, 2026
In vitro modeling of neuronal disorders using transfected primary neurons is one of the fundamental approaches for studying disease mechanisms and therapeutic screening. Assessing neuronal viability is an everyday yet critical task in such experiment...
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NetPolicy-RL: Network-Informed Offline Reinforcement Learning for Pharmacogenomic Drug Prioritization

bioRxiv Feb 2, 2026
Large-scale pharmacogenomic screens provide extensive measurements of drug response across diverse cancer cell lines; however, most computational approaches emphasize point-wise sensitivity prediction or static ranking, which are poorly aligned with ...
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Set-up, validation, evaluation, and cost-benefit analysis of an AI-assisted assessment of responsible research practices in a sample of life science publications

bioRxiv Feb 2, 2026
The (semi-)automated screening of publications for diverse quality and transparency criteria is at the core of systematic literature assessment. Typically, the assessment process involves two initial reviewers and one additional reviewer for cases th...
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MultiGEOmics: Graph-Based Integration of Multi-Omics via Biological Information Flows

bioRxiv Feb 2, 2026
Motivation: Multi-omics datasets capture complementary aspects of biological systems and are central to modern machine learning applications in biology and medicine. Existing graph-based integration methods typically construct separate graphs for eac...
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An Explainable Machine Learning Approach to study the positional significance of histone post-translational modifications in gene regulation

bioRxiv Feb 2, 2026
Epigenetic mechanisms regulate gene-expression by altering the structure of the chromatin without modifying the underlying DNA sequence. Histone post-translational modifications (PTMs) are critical epigenetic signals that influence transcriptional ac...
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G3DCT: An Interpretable Spatial Grid-based Framework with Temporal Convolution-Transformer for EEG Artifact Identification

bioRxiv Feb 2, 2026
Electroencephalography (EEG) serves as a fundamental tool in modern neurology, cognitive neuroscience, and brain-computer interfaces, but its practical application is often compromised by artifacts. Physiological artifacts are particularly intractabl...
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