AIMC Topic: Transcriptome

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Ensemble learning models that predict surface protein abundance from single-cell multimodal omics data.

Methods (San Diego, Calif.) Oct 9, 2020
Single-cell protein abundance is a fundamental type of information to characterize cell states. Due to high cost and technical barriers, however, direct quantification of proteins is difficult. Single-cell RNA sequencing (scRNA-seq) data, serving as ...
Computational Biology Sequence Analysis, RNA Membrane Proteins Gene Expression Regulation Humans Transcriptome Deep Learning Single-Cell Analysis
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Artificial Intelligence Applied to Gene Expression Testing (IVIGET) to Predict Trivalent Inactivated Influenza Vaccine Immunogenicity in HIV Infected Children.

Frontiers in immunology Oct 5, 2020
The number of patients affected by chronic diseases with special vaccination needs is burgeoning. In this scenario, predictive markers of immunogenicity, as well as signatures of immune responses are typically missing even though it would especially ...
Child Computational Biology Vaccination Coinfection Vaccines, Inactivated Reproducibility of Results Humans Influenza, Human Hemagglutination Inhibition Tests Gene Expression Profiling Artificial Intelligence Influenza Vaccines Transcriptome Prognosis HIV Infections Influenza A Virus, H1N1 Subtype Immunogenicity, Vaccine
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An embedded gene selection method using knockoffs optimizing neural network.

BMC bioinformatics Sep 22, 2020
BACKGROUND: Gene selection refers to find a small subset of discriminant genes from the gene expression profiles. How to select genes that affect specific phenotypic traits effectively is an important research work in the field of biology. The neural...
Computational Biology Zea mays Data Mining Gene Expression Regulation Humans Neural Networks, Computer Female Breast Neoplasms Transcriptome
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Machine learning predicts stem cell transplant response in severe scleroderma.

Annals of the rheumatic diseases Sep 15, 2020
OBJECTIVE: The Scleroderma: Cyclophosphamide or Transplantation (SCOT) trial demonstrated clinical benefit of haematopoietic stem cell transplant (HSCT) compared with cyclophosphamide (CYC). We mapped PBC (peripheral blood cell) samples from the SCOT...
Humans Machine Learning Female Adult Treatment Outcome Immunosuppressive Agents Hematopoietic Stem Cell Transplantation Cyclophosphamide Male Middle Aged Gene Expression Profiling Transcriptome Scleroderma, Diffuse
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A gene prioritization method based on a swine multi-omics knowledgebase and a deep learning model.

Communications biology Sep 10, 2020
The analyses of multi-omics data have revealed candidate genes for objective traits. However, they are integrated poorly, especially in non-model organisms, and they pose a great challenge for prioritizing candidate genes for follow-up experimental v...
Proteins Transcriptome Deep Learning Neural Networks, Computer Genomics Animals Databases, Genetic Swine
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Prediction Power on Cardiovascular Disease of Neuroimmune Guidance Cues Expression by Peripheral Blood Monocytes Determined by Machine-Learning Methods.

International journal of molecular sciences Sep 2, 2020
Atherosclerosis is the underlying pathology in a major part of cardiovascular disease, the leading cause of mortality in developed countries. The infiltration of monocytes into the vessel walls of large arteries is a key denominator of atherogenesis,...
Monocytes Ephrins Netrin-1 Semaphorins Middle Aged Transcriptome Humans Case-Control Studies Machine Learning Cohort Studies Biomarkers Female Adult Male Cardiovascular Diseases
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Machine learning based refined differential gene expression analysis of pediatric sepsis.

BMC medical genomics Aug 28, 2020
BACKGROUND: Differential expression (DE) analysis of transcriptomic data enables genome-wide analysis of gene expression changes associated with biological conditions of interest. Such analysis often provides a wide list of genes that are differentia...
Gene Expression Profiling Transcriptome Sepsis Child ROC Curve Gene Regulatory Networks Computational Biology Humans Machine Learning Biomarkers
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Progressive Multiple Sclerosis Transcriptome Deconvolution Indicates Increased M2 Macrophages in Inactive Lesions.

European neurology Aug 28, 2020
Accumulating evidence suggests M2 macrophages contribute to tissue reparation and limit inflammation in multiple sclerosis (MS). However, most studies have focused on murine models without substantial support through human MS observations. The presen...
Humans Machine Learning Macrophages Brain Female Adult Male Multiple Sclerosis, Chronic Progressive Middle Aged Transcriptome Inflammation White Matter
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Biomarkers of the Response to Immune Checkpoint Inhibitors in Metastatic Urothelial Carcinoma.

Frontiers in immunology Aug 25, 2020
The mechanisms underlying the resistance to immune checkpoint inhibitors (ICIs) therapy in metastatic urothelial carcinoma (mUC) patients are not clear. It is of great significance to discern mUC patients who could benefit from ICI therapy in clinica...
Urothelium Urinary Bladder Neoplasms Predictive Value of Tests Carcinoma Drug Resistance, Neoplasm Decision Support Techniques Nomograms Clinical Decision-Making Treatment Outcome Female Antibodies, Monoclonal, Humanized Risk Factors Transcriptome Humans Time Factors Biomarkers, Tumor Machine Learning Immune Checkpoint Inhibitors Male B7-H1 Antigen Risk Assessment Gene Expression Profiling
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Classifying Breast Cancer Subtypes Using Deep Neural Networks Based on Multi-Omics Data.

Genes Aug 4, 2020
With the high prevalence of breast cancer, it is urgent to find out the intrinsic difference between various subtypes, so as to infer the underlying mechanisms. Given the available multi-omics data, their proper integration can improve the accuracy o...
DNA Methylation DNA Copy Number Variations Mutation Breast Neoplasms Transcriptome Neural Networks, Computer Humans Gene Regulatory Networks Software Genomics Female
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