AIMC Topic: Transcriptome

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Applications of spatial transcriptomics and artificial intelligence to develop integrated management of pancreatic cancer.

Advances in cancer research Jul 9, 2024
Cancer is a complex disease intrinsically associated with cellular processes and gene expression. With the development of techniques such as single-cell sequencing and sequential fluorescence in situ hybridization (seqFISH), it was possible to map th...
Transcriptome Pancreatic Neoplasms Disease Management Humans Artificial Intelligence Machine Learning Tumor Microenvironment Biomarkers, Tumor Gene Expression Profiling
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Cross-attention enables deep learning on limited omics-imaging-clinical data of 130 lung cancer patients.

Cell reports methods Jul 8, 2024
Deep-learning tools that extract prognostic factors derived from multi-omics data have recently contributed to individualized predictions of survival outcomes. However, the limited size of integrated omics-imaging-clinical datasets poses challenges. ...
Prognosis Tomography, X-Ray Computed Female Humans Deep Learning Lung Neoplasms Gene Expression Regulation, Neoplastic Carcinoma, Non-Small-Cell Lung Biomarkers, Tumor Male Transcriptome
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Characterizing mitochondrial features in osteoarthritis through integrative multi-omics and machine learning analysis.

Frontiers in immunology Jul 4, 2024
PURPOSE: Osteoarthritis (OA) stands as the most prevalent joint disorder. Mitochondrial dysfunction has been linked to the pathogenesis of OA. The main goal of this study is to uncover the pivotal role of mitochondria in the mechanisms driving OA dev...
Computational Biology Multiomics Databases, Genetic Transcriptome Genome-Wide Association Study Gene Regulatory Networks Mitochondria Osteoarthritis Humans Machine Learning Gene Expression Profiling
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A deep-learning framework to predict cancer treatment response from histopathology images through imputed transcriptomics.

Nature cancer Jul 3, 2024
Advances in artificial intelligence have paved the way for leveraging hematoxylin and eosin-stained tumor slides for precision oncology. We present ENLIGHT-DeepPT, an indirect two-step approach consisting of (1) DeepPT, a deep-learning framework that...
Treatment Outcome Humans Gene Expression Profiling Precision Medicine Transcriptome Neoplasms Deep Learning
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A variational autoencoder trained with priors from canonical pathways increases the interpretability of transcriptome data.

PLoS computational biology Jul 3, 2024
Interpreting transcriptome data is an important yet challenging aspect of bioinformatic analysis. While gene set enrichment analysis is a standard tool for interpreting regulatory changes, we utilize deep learning techniques, specifically autoencoder...
Humans Algorithms Deep Learning Computational Biology Gene Expression Profiling Transcriptome
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Exploration and verification a 13-gene diagnostic framework for ulcerative colitis across multiple platforms via machine learning algorithms.

Scientific reports Jul 1, 2024
Ulcerative colitis (UC) is a chronic inflammatory bowel disease with intricate pathogenesis and varied presentation. Accurate diagnostic tools are imperative to detect and manage UC. This study sought to construct a robust diagnostic model using gene...
Biomarkers Female Adult Humans Machine Learning Case-Control Studies Male Algorithms Colitis, Ulcerative Gene Expression Profiling Lipocalin-2 Transcriptome Interleukin-1 Receptor-Associated Kinases
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Integrating machine learning algorithms and multiple immunohistochemistry validation to unveil novel diagnostic markers based on costimulatory molecules for predicting immune microenvironment status in triple-negative breast cancer.

Frontiers in immunology Jun 28, 2024
INTRODUCTION: Costimulatory molecules are putative novel targets or potential additions to current available immunotherapy, but their expression patterns and clinical value in triple-negative breast cancer (TNBC) are to be clarified.
Immunohistochemistry Machine Learning Algorithms Humans Female Biomarkers, Tumor Immunotherapy Tumor Microenvironment Triple Negative Breast Neoplasms Gene Expression Profiling Lymphocytes, Tumor-Infiltrating Transcriptome
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ST-CellSeg: Cell segmentation for imaging-based spatial transcriptomics using multi-scale manifold learning.

PLoS computational biology Jun 27, 2024
Spatial transcriptomics has gained popularity over the past decade due to its ability to evaluate transcriptome data while preserving spatial information. Cell segmentation is a crucial step in spatial transcriptomic analysis, as it enables the avoid...
Image Processing, Computer-Assisted Computational Biology Humans Machine Learning Algorithms Gene Expression Profiling Transcriptome
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Identification and validation of cuproptosis-related genes in acetaminophen-induced liver injury using bioinformatics analysis and machine learning.

Frontiers in immunology Jun 27, 2024
BACKGROUND: Acetaminophen (APAP) is commonly used as an antipyretic analgesic. However, acetaminophen overdose may contribute to liver injury and even liver failure. Acetaminophen-induced liver injury (AILI) is closely related to mitochondrial oxidat...
Machine Learning Animals Transcriptome Protein Interaction Maps Acetaminophen Mice, Inbred C57BL Mice Male Chemical and Drug Induced Liver Injury Liver Gene Expression Profiling Computational Biology Copper Disease Models, Animal
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Integrated machine learning identifies a cellular senescence-related prognostic model to improve outcomes in uterine corpus endometrial carcinoma.

Frontiers in immunology Jun 27, 2024
BACKGROUND: Uterine Corpus Endometrial Carcinoma (UCEC) stands as one of the prevalent malignancies impacting women globally. Given its heterogeneous nature, personalized therapeutic approaches are increasingly significant for optimizing patient outc...
Endometrial Neoplasms Transcriptome Gene Expression Regulation, Neoplastic Cellular Senescence Biomarkers, Tumor Middle Aged Gene Expression Profiling Humans Female Tumor Microenvironment Machine Learning Prognosis
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