bioRxiv

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Fast segmentation with the NextBrain histological atlas

bioRxiv Jan 1, 2025
Structural brain analysis at the subregion level offers critical insights into healthy aging and neurodegenerative diseases. The NextBrain histological atlas was recently introduced to support such fine-grained investigations, but its existing Bayesi...
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Variational autoencoder for interpretable seizure onset phases detection

bioRxiv Jan 1, 2025
In this study, we describe a deep learning framework for automated seizure annotation in stereo electroencephalography (SEEG) data of patients with focal epilepsy. We use a one-dimensional Variational Autoencoder (VAE) for feature extraction of singl...
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A Modular Fusion Neural Network Approach to Efficiently Predict Multi-Metal Binding Sites in Protein Sequences

bioRxiv Jan 1, 2025
Accurate identification of metal-binding residues is essential for the study of metalloproteins, like zinc finger proteins, haemoglobin, and DNA polymerase. Due to the high cost and time demands of experimental methods, computational prediction has b...
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EpiFoundation: A Foundation Model for Single-Cell ATAC-seq via Peak-to-Gene Alignment

bioRxiv Jan 1, 2025
Foundation models exhibit strong capabilities for downstream tasks by learning generalized representations through self-supervised pre-training on large datasets. While several foundation models have been developed for single-cell RNA-seq (scRNA-seq)...
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PlasticEnz: An integrated database and screening tool combining homology and machine learning to identify plastic-degrading enzymes in meta-omics datasets

bioRxiv Jan 1, 2025
PlasticEnz is a new open-source tool for detecting plastic-degrading enzymes (plastizymes) in metagenomic data by combining sequence homology-based search with machine learning. It integrates custom Hidden Markov Models, DIAMOND alignments, and polym...
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A Convolutional Deep Learning Approach to identify DNA Sequences for Gene Prediction

bioRxiv Jan 1, 2025
In this work, we present a highly efficient machine learning method for identifying DNA sequences that code for genes. The learning process is based on Human Genome Build 38 (GRCh38) sequences extracted from various specialized databases. The sequenc...
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ComplexMatrixComb: Predicting Drug Combination IC50 Doses via Complex Numbers and Matrix Factorization

bioRxiv Jan 1, 2025
Determining precise drug concentrations to inhibit cancer cell growth is a critical but resource-intensive challenge, especially for combinations requiring many dose pairs. Existing computational methods often predict synergy or classify interactions...
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Machine learning-based definition of cellular senescence reveals pro-senescence potential implication in lung adenocarcinoma

bioRxiv Jan 1, 2025
Despite growing evidence implicating cellular senescence in tumor progression, methodological challenges in objectively quantifying senescent cell burden across cancer types continue to limit mechanistic studies and clinical translation. To address t...
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Functional Group Composition: The Blueprint for Protein Interactions

bioRxiv Jan 1, 2025
Understanding the complex landscape of protein interactions, especially those involving intrinsically disordered proteins (IDPs), is fundamental yet challenging due to their structural heterogeneity and flexibility. Traditional sequence-based homolog...
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Enhancer-AAVs allow genetic access to oligodendrocytes and diverse populations of astrocytes across species

bioRxiv Jan 1, 2025
Proper brain function requires the assembly and function of diverse populations of neurons and glia. Single cell gene expression studies have mostly focused on characterization of neuronal cell diversity; however, recent studies have also revealed su...
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