AIMC Topic: Transcriptome

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Machine learning analysis of gene expression profile reveals a novel diagnostic signature for osteoporosis.

Journal of orthopaedic surgery and research Mar 15, 2021
BACKGROUND: Osteoporosis (OP) is increasingly prevalent with the aging of the world population. It is urgent to identify efficient diagnostic signatures for the clinical application.
Transcriptome Protein Interaction Maps RNA, Messenger Logistic Models Osteoporosis Female Male Gene Expression Profiling Potassium Channels CD5 Antigens Lymphocyte Specific Protein Tyrosine Kinase p56(lck) Signaling Lymphocytic Activation Molecule Family Humans Machine Learning
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Virtual Transcriptomics: Noninvasive Phenotyping of Atherosclerosis by Decoding Plaque Biology From Computed Tomography Angiography Imaging.

Arteriosclerosis, thrombosis, and vascular biology Mar 11, 2021
[Figure: see text].
Humans Artificial Intelligence Phenotype Female Aged Coronary Artery Disease Models, Genetic Feasibility Studies Oligonucleotide Array Sequence Analysis Predictive Value of Tests Coronary Vessels Computed Tomography Angiography Plaque, Atherosclerotic Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Male Gene Expression Profiling Transcriptome Pilot Projects
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Expanding the drug discovery space with predicted metabolite-target interactions.

Communications biology Mar 5, 2021
Metabolites produced in the human gut are known modulators of host immunity. However, large-scale identification of metabolite-host receptor interactions remains a daunting challenge. Here, we employed computational approaches to identify 983 potenti...
Transcriptome Protein Interaction Maps Bacteria Signal Transduction Databases, Factual Humans Inflammatory Bowel Diseases Machine Learning Drug Discovery Cells, Cultured Gene Expression Profiling Gastrointestinal Agents Gastrointestinal Microbiome Data Mining Ligands Metabolomics Molecular Targeted Therapy Metabolome Host-Pathogen Interactions Anti-Inflammatory Agents
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Predicting dynamic cellular protein-RNA interactions by deep learning using in vivo RNA structures.

Cell research Feb 23, 2021
Interactions with RNA-binding proteins (RBPs) are integral to RNA function and cellular regulation, and dynamically reflect specific cellular conditions. However, presently available tools for predicting RBP-RNA interactions employ RNA sequence and/o...
Humans Transcriptome Binding Sites Deep Learning Protein Binding RNA-Binding Proteins RNA
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CKLF and IL1B transcript levels at diagnosis are predictive of relapse in children with pre-B-cell acute lymphoblastic leukaemia.

British journal of haematology Feb 23, 2021
Disease relapse is the greatest cause of treatment failure in paediatric B-cell acute lymphoblastic leukaemia (B-ALL). Current risk stratifications fail to capture all patients at risk of relapse. Herein, we used a machine-learning approach to identi...
Male Humans Risk Assessment Machine Learning Infant Adolescent Child Female Transcriptome Child, Preschool Predictive Value of Tests Acute Disease Interleukin-1beta Recurrence Survival Analysis Precursor B-Cell Lymphoblastic Leukemia-Lymphoma Treatment Failure MARVEL Domain-Containing Proteins Chemokines
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Integrated Learning: Screening Optimal Biomarkers for Identifying Preeclampsia in Placental mRNA Samples.

Computational and mathematical methods in medicine Feb 23, 2021
Preeclampsia (PE) is a maternal disease that causes maternal and child death. Treatment and preventive measures are not sound enough. The problem of PE screening has attracted much attention. The purpose of this study is to screen placental mRNA to o...
Algorithms Biomarkers Pregnancy Female Humans Neural Networks, Computer Databases, Nucleic Acid Machine Learning Decision Trees Placenta Genetic Testing Transcriptome Genetic Markers Diagnosis, Computer-Assisted Pre-Eclampsia Computational Biology RNA, Messenger
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Machine Learning Identifies Complicated Sepsis Course and Subsequent Mortality Based on 20 Genes in Peripheral Blood Immune Cells at 24 H Post-ICU Admission.

Frontiers in immunology Feb 22, 2021
A complicated clinical course for critically ill patients admitted to the intensive care unit (ICU) usually includes multiorgan dysfunction and subsequent death. Owing to the heterogeneity, complexity, and unpredictability of the disease progression,...
Chromosome Mapping Time Factors Reproducibility of Results Databases, Genetic Humans Hospital Mortality Leukocytes Gene Expression Profiling Machine Learning ROC Curve Critical Care Transcriptome Computational Biology Biomarkers Disease Susceptibility Sepsis Intensive Care Units
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Potential applications of deep learning in single-cell RNA sequencing analysis for cell therapy and regenerative medicine.

Stem cells (Dayton, Ohio) Feb 15, 2021
When used in cell therapy and regenerative medicine strategies, stem cells have potential to treat many previously incurable diseases. However, current application methods using stem cells are underdeveloped, as these cells are used directly regardle...
Transcriptome Deep Learning Single-Cell Analysis RNA-Seq Regenerative Medicine Cell- and Tissue-Based Therapy Humans
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CNAPE: A Machine Learning Method for Copy Number Alteration Prediction from Gene Expression.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2021
Detection of DNA copy number alteration in cancer cells is critical to understanding cancer initiation and progression. Widely used methods, such as DNA arrays and genomic DNA sequencing, are relatively expensive and require DNA samples at a microgra...
Transcriptome Computational Biology DNA Copy Number Variations Humans Machine Learning Neoplasms
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A Deep Learning Framework for Identifying Essential Proteins by Integrating Multiple Types of Biological Information.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2021
Computational methods including centrality and machine learning-based methods have been proposed to identify essential proteins for understanding the minimum requirements of the survival and evolution of a cell. In centrality methods, researchers are...
Deep Learning Protein Interaction Maps Computational Biology Protein Interaction Mapping Transcriptome Saccharomyces cerevisiae Proteins Intracellular Space
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