AIMC Topic: Transcriptome

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Evaluation of Clinically Significant miRNAs Level by Machine Learning Approaches Utilizing Total Transcriptome Data.

Doklady. Biochemistry and biophysics Mar 27, 2024
Analysis of the mechanisms underlying the occurrence and progression of cancer represents a key objective in contemporary clinical bioinformatics and molecular biology. Utilizing omics data, particularly transcriptomes, enables a detailed characteriz...
Gene Expression Regulation, Neoplastic MicroRNAs Gene Expression Profiling Transcriptome Machine Learning Neoplasms Humans
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TENET: Triple-enhancement based graph neural network for cell-cell interaction network reconstruction from spatial transcriptomics.

Journal of molecular biology Mar 18, 2024
Cellular communication relies on the intricate interplay of signaling molecules, forming the Cell-cell Interaction network (CCI) that coordinates tissue behavior. Researchers have shown the capability of shallow neural networks in reconstructing CCI,...
Neural Networks, Computer Transcriptome Computational Biology Algorithms Gene Expression Profiling Cell Communication
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Exploring Prognostic Gene Factors in Breast Cancer via Machine Learning.

Biochemical genetics Feb 21, 2024
Breast cancer remains the most prevalent cancer in women. To date, its underlying molecular mechanisms have not been fully uncovered. The determination of gene factors is important to improve our understanding on breast cancer, which can correlate th...
Gene Expression Regulation, Neoplastic Gene Expression Profiling Transcriptome Breast Neoplasms Humans Biomarkers, Tumor Machine Learning Prognosis Female Algorithms
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Deep learning-based quantification and transcriptomic profiling reveal a methyl jasmonate-mediated glandular trichome formation pathway in Cannabis sativa.

The Plant journal : for cell and molecular biology Feb 8, 2024
Cannabis glandular trichomes (GTs) are economically and biotechnologically important structures that have a remarkable morphology and capacity to produce, store, and secrete diverse classes of secondary metabolites. However, our understanding of the ...
Gene Expression Regulation, Plant Trichomes Oxylipins Cannabis Plant Growth Regulators Cyclopentanes Gene Expression Profiling Deep Learning Acetates Transcriptome
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Enabling personalised disease diagnosis by combining a patient's time-specific gene expression profile with a biomedical knowledge base.

BMC bioinformatics Feb 7, 2024
BACKGROUND: Recent developments in the domain of biomedical knowledge bases (KBs) open up new ways to exploit biomedical knowledge that is available in the form of KBs. Significant work has been done in the direction of biomedical KB creation and KB ...
Machine Learning Algorithms Transcriptome Humans Knowledge Bases
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CIRI-Deep Enables Single-Cell and Spatial Transcriptomic Analysis of Circular RNAs with Deep Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Feb 2, 2024
Circular RNAs (circRNAs) are a crucial yet relatively unexplored class of transcripts known for their tissue- and cell-type-specific expression patterns. Despite the advances in single-cell and spatial transcriptomics, these technologies face difficu...
RNA Transcriptome RNA, Circular Gene Expression Profiling Deep Learning
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Compound Activity Prediction with Dose-Dependent Transcriptomic Profiles and Deep Learning.

Journal of chemical information and modeling Jan 31, 2024
Predicting compound activity in assays is a long-standing challenge in drug discovery. Computational models based on compound-induced gene expression signatures from a single profiling assay have shown promise toward predicting compound activity in o...
Malaria Humans Transcriptome Deep Learning Drug Discovery Gene Expression Profiling
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Novel gene signatures predicting and immune infiltration analysis in Parkinson's disease: based on combining random forest with artificial neural network.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology Jan 24, 2024
BACKGROUND: Parkinson's disease (PD) ranks as the second most prevalent neurodegenerative disorder globally, and its incidence is rapidly rising. The diagnosis of PD relies on clinical characteristics. Although current treatments aim to alleviate sym...
Humans Machine Learning Gene Expression Profiling Neural Networks, Computer Mast Cells Parkinson Disease Transcriptome Random Forest Computational Biology
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Time-Course Transcriptome Analysis Reveals Distinct Phases and Identifies Two Key Genes during Severe Fever with Thrombocytopenia Syndrome Virus Infection in PMA-Induced THP-1 Cells.

Viruses Dec 29, 2023
In recent years, there have been significant advancements in the research of Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV). However, several limitations and challenges still exist. For instance, researchers face constraints regarding expe...
Severe Fever with Thrombocytopenia Syndrome Transcriptome THP-1 Cells Cluster Analysis Humans Gene Expression Profiling
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Identifying multi-target drugs for prostate cancer using machine learning-assisted transcriptomic analysis.

Journal of biomolecular structure & dynamics Dec 16, 2023
Prostate cancer is a leading cause of cancer death in men, and the development of effective treatments is of great importance. This study explored to identify the candidate drugs for prostate cancer by transcriptomic data and CMap database analysis. ...
Gene Expression Profiling Machine Learning Transcriptome Male Cell Line, Tumor Drug Discovery Prostatic Neoplasms Humans Antineoplastic Agents Gene Expression Regulation, Neoplastic Bisoprolol Cell Proliferation
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