AIMC Topic: Transcription Factors

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Interpreting regulatory mechanisms of Hippo signaling through a deep learning sequence model.

Cell genomics Apr 1, 2025
Signaling pathway components are well studied, but how they mediate cell-type-specific transcription responses is an unresolved problem. Using the Hippo pathway in mouse trophoblast stem cells as a model, we show that the DNA binding of signaling eff...
Protein Binding Mice Signal Transduction Transcription Factors Animals Deep Learning Phosphoproteins Trophoblasts Enhancer Elements, Genetic Muscle Proteins Protein Serine-Threonine Kinases Adaptor Proteins, Signal Transducing DNA-Binding Proteins Molecular Dynamics Simulation Hippo Signaling Pathway YAP-Signaling Proteins TEA Domain Transcription Factors
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Deep Neural Network-Mining of Rice Drought-Responsive TF-TAG Modules by a Combinatorial Analysis of ATAC-Seq and RNA-Seq.

Plant, cell & environment Mar 31, 2025
Drought is a critical risk factor that impacts rice growth and yields. Previous studies have focused on the regulatory roles of individual transcription factors in response to drought stress. However, there is limited understanding of multi-factor st...
Neural Networks, Computer RNA-Seq Gene Regulatory Networks Stress, Physiological Transcription Factors Gene Expression Regulation, Plant Oryza Droughts Data Mining Chromatin Immunoprecipitation Sequencing Plant Proteins
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CacPred: a cascaded convolutional neural network for TF-DNA binding prediction.

BMC genomics Mar 18, 2025
BACKGROUND: Transcription factors (TFs) regulate the genes' expression by binding to DNA sequences. Aligned TFBSs of the same TF are seen as cis-regulatory motifs, and substantial computational efforts have been invested to find motifs. In recent yea...
Chromatin Immunoprecipitation Sequencing Software Algorithms Convolutional Neural Networks Protein Binding Computational Biology Transcription Factors DNA Binding Sites Neural Networks, Computer
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Transfer learning reveals sequence determinants of the quantitative response to transcription factor dosage.

Cell genomics Feb 27, 2025
Deep learning models have advanced our ability to predict cell-type-specific chromatin patterns from transcription factor (TF) binding motifs, but their application to perturbed contexts remains limited. We applied transfer learning to predict how co...
Transcription Factors Binding Sites Chromatin Nucleosomes SOX9 Transcription Factor Animals Deep Learning Protein Binding Mice Humans
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Identification of Biomarkers for Response to Interferon in Chronic Hepatitis B Based on Bioinformatics Analysis and Machine Learning.

Viral immunology Feb 24, 2025
Interferon (IFN) is a pivotal agent against hepatitis B virus (HBV) in clinic, but there is a lack of accurate biomarkers to predict the response to IFN therapy in patients with chronic hepatitis B (CHB). Our study aimed to investigate potential targ...
Humans Machine Learning Biomarkers MicroRNAs Hepatitis B, Chronic Gene Regulatory Networks Interferons Computational Biology Gene Expression Profiling RNA, Messenger Antiviral Agents Transcription Factors Hepatitis B virus Protein Interaction Maps
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Identification of biomarkers associated with phagocytosis regulatory factors in coronary artery disease using machine learning and network analysis.

Mammalian genome : official journal of the International Mammalian Genome Society Feb 14, 2025
BACKGROUND: Coronary artery disease (CAD) is the leading cause of death worldwide, and aberrant phagocytosis may be involved in its development. Understanding this aspect may provide new avenues for prompt CAD diagnosis.
Syk Kinase Coronary Artery Disease Phagocytosis Receptors, IgG Toll-Like Receptor 2 Protein Interaction Maps Gene Regulatory Networks Polymorphism, Single Nucleotide Humans Computational Biology Transcription Factors Machine Learning Databases, Genetic Biomarkers MicroRNAs Gene Expression Profiling Interleukin-1beta
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Galactose-Induced Cataracts in Rats: A Machine Learning Analysis.

International journal of medical sciences Feb 10, 2025
Rat models are widely used to study cataracts due to their cost-effectiveness and prominent physiological and genetic similarities to humans The objective of this study was to identify genes involved in cataractogenesis due to galactose exposure in ...
Disease Models, Animal Male Cataract Galactose Humans Gene Expression Profiling Lens, Crystalline Machine Learning Rats Gene Expression Regulation Animals Transcription Factors
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A mechanism-informed deep neural network enables prioritization of regulators that drive cell state transitions.

Nature communications Feb 3, 2025
Cells are regulated at multiple levels, from regulations of individual genes to interactions across multiple genes. Some recent neural network models can connect molecular changes to cellular phenotypes, but their design lacks modeling of regulatory ...
Transcription Factors Gene Expression Regulation Hair Follicle Gene Regulatory Networks Mice Humans Polymorphism, Single Nucleotide Neural Networks, Computer Animals Diabetes Mellitus, Type 2 Single-Cell Analysis
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Machine learning-driven identification of critical gene programs and key transcription factors in migraine.

The journal of headache and pain Jan 20, 2025
BACKGROUND: Migraine is a complex neurological disorder characterized by recurrent episodes of severe headaches. Although genetic factors have been implicated, the precise molecular mechanisms, particularly gene expression patterns in migraine-associ...
Polymorphism, Single Nucleotide Transcription Factors Migraine Disorders Genome-Wide Association Study Gene Regulatory Networks Humans Genetic Predisposition to Disease Machine Learning Gene Expression Profiling
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Interpretable identification of cancer genes across biological networks via transformer-powered graph representation learning.

Nature biomedical engineering Jan 9, 2025
Graph representation learning has been leveraged to identify cancer genes from biological networks. However, its applicability is limited by insufficient interpretability and generalizability under integrative network analysis. Here we report the dev...
Humans MicroRNAs Computational Biology Machine Learning Genes, Neoplasm Algorithms Gene Expression Regulation, Neoplastic Neoplasms Transcription Factors Gene Regulatory Networks Databases, Genetic
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