AIMC Journal:
bioRxiv

Showing 1471 to 1480 of 4956 articles

Astrocytic D1 Dopamine-Signaling Regulates Synaptic Remodeling and Cocaine Seeking

bioRxiv May 18, 2026
D1-type receptor (D1R)-mediated dopaminergic signaling within the nucleus accumbens shell (NAcSh) is essential for forming adaptive circuit changes that embed persistent memories associated with drug seeking and craving. While D1R is expressed in bot...
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NeuroPupil: A generalization-first framework for scalable and biologically informative cross-species pupillometry

bioRxiv May 18, 2026
Quantitative pupillometry provides a noninvasive window into brain state and neurological function, but its broader use across experimental and clinical settings is limited by challenges in achieving accurate, scalable, and generalizable measurements...
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Machine learning-based decoding of emotional valence from electrophysiological signals in the monkey brain

bioRxiv May 18, 2026
Understanding how the brain operates in naturalistic settings requires methods that go beyond conventional repeated-measurement approaches, necessitating the development of single-trial neural activity analysis. Recent advances in machine learning of...
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Interpretable Predictive Modeling for Medical Data Using Boolean Rule-aware Regression

bioRxiv May 18, 2026
Purpose: In clinical practice, accurate prediction of disease risk must be accompanied by transparent, human-understandable explanations to support diagnostic confidence, guide therapeutic decisions, and meet ethical and regulatory standards. While d...
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A Multimodal Neural Network Model for Early Recurrence Prediction in Lung Adenocarcinoma

bioRxiv May 18, 2026
Lung adenocarcinoma (LUAD), a subtype of non-small cell lung cancer (NSCLC), is the most common primary lung cancer worldwide. Despite advancements in early detection and treatment, up to 39% of patients develop recurrent tumors following complete re...
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Learning Chirality-Aware Representations to Predict Drug Side Effect Frequencies

bioRxiv May 18, 2026
Ab initio prediction of side effect frequencies is important for assessing the risk-benefit profile of drugs and for identifying potential adverse effects early in development. A key challenge is chirality: many drugs exist as enantiomers, pairs of m...
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Stereochemistry-Aware Drug-Target Affinity Prediction

bioRxiv May 18, 2026
Drug-target affinity (DTA) prediction is a key task in drug discovery, enabling the estimation of the interaction strength between candidate compounds and biological targets. However, current models rely on connectivity-based molecular representation...
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DamageFormer: a damage-aware multimodal deep learning framework for DNA lesion identification from nanopore sequencing

bioRxiv May 18, 2026
Background: DNA lesions arise from endogenous metabolism and environmental exposure and are the major drivers of mutagenesis, aging, and cancer development. However, mapping DNA damage at nucleotide resolution remains a technically challenging task. ...
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Multivariate Bayesian Inversion for Classification and Regression

bioRxiv May 18, 2026
We propose the statistical modelling approach to supervised learning (i.e. predicting labels from features) as an alternative to algorithmic machine learning (ML). The approach is demonstrated by employing a multivariate general linear model (MGLM) d...
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petVAE: A Data-Driven Model for Identifying Amyloid PET Subgroups Across the Alzheimer's Disease Continuum

bioRxiv May 18, 2026
Amyloid-{beta} (A{beta}) PET imaging is a core biomarker and is sufficient for the biological diagnosis of Alzheimer's disease (AD). Here, we aimed to identify biologically meaningful subgroups across the continuum of A{beta} accumulation using a dat...
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