bioRxiv

Showing 4961 to 4970 of 5029 articles

Synthesizing images to map neural networks to the human brain

bioRxiv Jan 1, 2025
Computational models can be used to generate hypotheses about the brain. In the visual system, this approach has revealed similarities between how natural images are represented in convolutional neural networks and in cortical regions. However, natur...
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DCBK: A Fragment-Based Hybrid Simulation and Machine Learning Framework for Predicting Ligand Dissociation Kinetics

bioRxiv Jan 1, 2025
Predicting small-molecule binding kinetics is central to drug discovery, but accurately estimating dissociation rates (koff) remains challenging due to high energy barriers and the high computational cost of conventional simulations. Here, we present...
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AstraBIND: Graph Attention Network for Predicting Ligand Binding Sites

bioRxiv Jan 1, 2025
Predicting ligand binding sites is central to computational biology and drug discovery. Existing machine learning approaches either use protein sequence, structure, or both. While structure-based deep learning models typically outperform sequence-bas...
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Improving DNA Modeling with WaveDNA: Enhancing Speed, Generalizability, and Interpretability through Wavelet Transformation

bioRxiv Jan 1, 2025
Transcription factors (TFs) regulate gene expression by binding to short, specific DNA sequences, known as transcription factor binding sites (TFBSs). Accurate identification of TFBSs is fundamental for understanding transcriptional regulation. By le...
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Batch-Harmonized Machine Learning Framework for Cross-Cohort RNA Biomarker Discovery in Pancreatic Adenocarcinoma

bioRxiv Jan 1, 2025
Pancreatic ductal adenocarcinoma (PDAC) lacks reliable prognostic biomarkers. RNA-based signatures suffer from poor reproducibility due to batch effects and platform heterogeneity between microarray and RNA-seq data, limiting machine learning applica...
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Decoding Gene Responsiveness to Synthetic Chromatin Reader-Actuators with Multi-Modal Epigenomic Profiling

bioRxiv Jan 1, 2025
Cell identity is regulated by chromatin states that encode gene regulatory memory and shape responses to new inputs. To investigate how chromatin context influences inducibility in differentiated cells, we employed engineered synthetic reader-actuato...
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Machine Learning-Driven Discovery of Synergistic Protein Interactions Identifies ATL3 as a Putative Biomarker for Cancer Drug Response

bioRxiv Jan 1, 2025
Resistance to targeted molecular therapies—both primary and acquired—remains a major obstacle to effective cancer treatment. Despite extensive research, the molecular determinants of treatment resistance are still incompletely understood, underscorin...
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Deep-Pose-Tracker: a unified model for behavioural studies of Caenorhabditis elegans

bioRxiv Jan 1, 2025
Tracking and analyzing animal behaviour is a crucial step in fields such as neuro-science and developmental biology. Behavioral studies in the nematode C. elegans, for example, help in understanding how organisms respond to external cues and how the ...
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RegFormer: A Single-Cell Foundation Model Powered by Gene Regulatory Hierarchies

bioRxiv Jan 1, 2025
Single-cell RNA sequencing (scRNA-seq) enables high-resolution profiling of cellular diversity, but current computational models often fail to incorporate regulatory priors, handle data sparsity, or efficiently process long gene sequences. Here, we p...
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Deep Learning for Cognitive Task Presence Prediction from Dynamic Functional Connectivity

bioRxiv Jan 1, 2025
Dynamic functional connectivity (dFC) studies the time-varying coordination between brain regions measured with fMRI and is a potential biomarker for understanding cognitive dynamics and tracking the development of neurological disorders. However, a ...
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