AIMC Journal:
bioRxiv

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A New Paradigm for Genome-wide DNA Methylation Prediction Without Methylation Input

bioRxiv Feb 17, 2026
DNA methylation (DNAm) is a key epigenetic modification that regulates gene expression and is pivotal in development and disease. However, profiling DNAm at genome scale is challenging: of ~28 million CpG sites in the human genome, only about 1-3% ar...
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Fast-cWDM Brain MRI: Fast Conditional Wavelet Diffusion Model for Synthesis Brain MRI Modality

bioRxiv Feb 17, 2026
In this paper, we present a novel and efficient framework for cross-modality medical image synthesis, developed for BraSyn-Task 8. Our method combines the fast-sampling capabilities of the Fast-Denoising Diffusion Probabilistic Model (Fast-DDPM) with...
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RNAiSpline: A Deep learning model for siRNA efficacy prediction

bioRxiv Feb 17, 2026
RNA interference (RNAi) is a crucial biological post-transcriptional gene silencing mechanism where small interfering RNA (siRNA) guides RNA-induced silencing complex (RISC) to bind with messenger RNA (mRNA) thereby silencing it and stopping protein ...
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A Pan-Cancer Ex Vivo Drug Screen Atlas for Functional Precision Oncology

bioRxiv Feb 17, 2026
Compared to immortalized cell lines, patient-derived organoids and other ex vivo models have been shown to better recapitulate patient responses to therapy. High cost and technical complexity have prevented the creation of pan-cancer ex vivo datasets...
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Automated AI image recognition tools improve the efficiency of aerial wildlife counts: A multi-species case study on breeding seabirds and pinnipeds at the sub-Antarctic Bounty Islands.

bioRxiv Feb 17, 2026
Accurate monitoring of populations is essential for conservation management, including for vulnerable seabirds. Yet traditional ground-based surveys are logistically challenging and time-consuming, especially in remote environments such as the sub-An...
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Evaluating Single-Cell Perturbation Response Models Is Far from Straightforward

bioRxiv Feb 17, 2026
Predicting cellular responses to genetic and chemical perturbations remains a central challenge in single-cell biology and a key step toward building in silico virtual cells. The rapid growth of perturbation datasets and advances in deep-learning mod...
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Wavelet-Domain Multi-Representation and Ensemble Learning for Automated ECG Analysis

bioRxiv Feb 17, 2026
Accurate diagnosis of cardiac abnormalities from electrocardiogram signals remains a central challenge in automated cardiovascular assessment. This study investigates the efficiency of time-frequency representations and deep learning architectures in...
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MicrowellMicrofluidicsMiner (M3): Leverage Large Language Model Agents for Knowledge Mining of Microwell Microfluidics

bioRxiv Feb 17, 2026
Microwell microfluidics has emerged as powerful platforms for high precision biological and chemical investigations, bridging microscale fluid handling with compartmentalized reaction environments. Achieving robust and reproducible performance in suc...
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Sparse mixed codes on shared manifolds for human-like spatial attention in artificial neural networks

bioRxiv Feb 17, 2026
Spatial attention is often partitioned into endogenous, exogenous, and social forms, yet it remains unclear whether a single neural circuit can support all three and how their population codes are organized. Here we trained recurrent artificial neura...
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p-Brain: An Automated MRI Pipeline for Cerebral Perfusion, Microvasculature, and Blood-Brain Barrier Permeability Estimation

bioRxiv Feb 17, 2026
We present p-Brain, an end-to-end neuroimaging analysis framework for reproducible, automated quantitative DCE-MRI analysis at scale. From standard acquisitions, p-Brain estimates baseline relaxation parameters, converts signal to gadolinium concentr...
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