AIMC Topic: Transcriptome

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A first perturbome of Pseudomonas aeruginosa: Identification of core genes related to multiple perturbations by a machine learning approach.

Bio Systems Mar 20, 2021
Tolerance to stress conditions is vital for organismal survival, including bacteria under specific environmental conditions, antibiotics, and other perturbations. Some studies have described common modulation and shared genes during stress response t...
Genomics Principal Component Analysis Models, Biological Pseudomonas aeruginosa Genes, Bacterial Stress, Physiological Machine Learning Algorithms Transcriptome
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Deep generative neural network for accurate drug response imputation.

Nature communications Mar 19, 2021
Drug response differs substantially in cancer patients due to inter- and intra-tumor heterogeneity. Particularly, transcriptome context, especially tumor microenvironment, has been shown playing a significant role in shaping the actual treatment outc...
Gene Expression Regulation, Neoplastic Pharmaceutical Preparations Antineoplastic Agents Transcriptome Deep Learning Cell Line, Tumor Humans Neural Networks, Computer Tumor Microenvironment Neoplasms
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Integrated multi-omics analysis of ovarian cancer using variational autoencoders.

Scientific reports Mar 18, 2021
Cancer is a complex disease that deregulates cellular functions at various molecular levels (e.g., DNA, RNA, and proteins). Integrated multi-omics analysis of data from these levels is necessary to understand the aberrant cellular functions accountab...
Cluster Analysis Ovarian Neoplasms Kaplan-Meier Estimate Female Gene Expression Profiling Transcriptome Deep Learning Cohort Studies Genomics Computational Biology Epigenesis, Genetic Epigenomics Humans Data Analysis Prognosis
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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.
Machine Learning Osteoporosis Female Male Gene Expression Profiling Humans CD5 Antigens Lymphocyte Specific Protein Tyrosine Kinase p56(lck) Signaling Lymphocytic Activation Molecule Family Transcriptome Protein Interaction Maps RNA, Messenger Logistic Models Potassium Channels
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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 Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Feasibility Studies Phenotype Gene Expression Profiling Coronary Vessels Transcriptome Female Plaque, Atherosclerotic Pilot Projects Aged Oligonucleotide Array Sequence Analysis Models, Genetic Male Computed Tomography Angiography Predictive Value of Tests
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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...
Drug Discovery Gene Expression Profiling Transcriptome Protein Interaction Maps Bacteria Machine Learning Cells, Cultured Databases, Factual Inflammatory Bowel Diseases Gastrointestinal Agents Data Mining Ligands Molecular Targeted Therapy Host-Pathogen Interactions Signal Transduction Gastrointestinal Microbiome Humans Metabolomics Metabolome 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...
Binding Sites Humans Transcriptome 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...
Risk Assessment Infant Transcriptome Adolescent Child, Preschool Child Predictive Value of Tests Interleukin-1beta Acute Disease Precursor B-Cell Lymphoblastic Leukemia-Lymphoma Survival Analysis Humans MARVEL Domain-Containing Proteins Treatment Failure Machine Learning Chemokines Female Recurrence Male
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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...
Pregnancy Genetic Markers Neural Networks, Computer RNA, Messenger Pre-Eclampsia Humans Female Machine Learning Decision Trees Databases, Nucleic Acid Placenta Algorithms Transcriptome Genetic Testing Diagnosis, Computer-Assisted Biomarkers Computational Biology
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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,...
Hospital Mortality ROC Curve Reproducibility of Results Computational Biology Leukocytes Humans Databases, Genetic Gene Expression Profiling Critical Care Machine Learning Transcriptome Disease Susceptibility Biomarkers Sepsis Chromosome Mapping Intensive Care Units Time Factors
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