AIMC Topic: Gene Expression Regulation

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SGANRDA: semi-supervised generative adversarial networks for predicting circRNA-disease associations.

Briefings in bioinformatics Sep 2, 2021
Emerging research shows that circular RNA (circRNA) plays a crucial role in the diagnosis, occurrence and prognosis of complex human diseases. Compared with traditional biological experiments, the computational method of fusing multi-source biologica...
Humans Multiple Sclerosis Datasets as Topic Gene Expression Regulation RNA, Circular Computational Biology Databases, Genetic Risk Factors Area Under Curve Neoplasms Myocardial Infarction Deep Learning Osteoarthritis Gene Regulatory Networks
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A sequence-based deep learning approach to predict CTCF-mediated chromatin loop.

Briefings in bioinformatics Sep 2, 2021
Three-dimensional (3D) architecture of the chromosomes is of crucial importance for transcription regulation and DNA replication. Various high-throughput chromosome conformation capture-based methods have revealed that CTCF-mediated chromatin loops a...
Nucleotide Motifs Chromatin CCCTC-Binding Factor Gene Expression Regulation Genome, Human Molecular Conformation K562 Cells Humans Neural Networks, Computer Software MCF-7 Cells Datasets as Topic
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A comprehensive overview and critical evaluation of gene regulatory network inference technologies.

Briefings in bioinformatics Sep 2, 2021
Gene regulatory network (GRN) is the important mechanism of maintaining life process, controlling biochemical reaction and regulating compound level, which plays an important role in various organisms and systems. Reconstructing GRN can help us to un...
Models, Genetic Escherichia coli Databases, Genetic Machine Learning Bayes Theorem Neoplasms Biomarkers, Tumor Gene Expression Regulation Transcriptome RNA-Seq Gene Regulatory Networks Computational Biology
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Modeling multi-species RNA modification through multi-task curriculum learning.

Nucleic acids research Apr 19, 2021
N6-methyladenosine (m6A) is the most pervasive modification in eukaryotic mRNAs. Numerous biological processes are regulated by this critical post-transcriptional mark, such as gene expression, RNA stability, RNA structure and translation. Recently, ...
Humans Machine Learning Software Animals RNA Datasets as Topic Gene Expression Regulation Adenosine Transcriptome RNA-Binding Proteins Sequence Analysis, RNA Databases, Genetic
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Merged Affinity Network Association Clustering: Joint multi-omic/clinical clustering to identify disease endotypes.

Cell reports Apr 13, 2021
Although clinical and laboratory data have long been used to guide medical practice, this information is rarely integrated with multi-omic data to identify endotypes. We present Merged Affinity Network Association Clustering (MANAclust), a coding-fre...
Humans Nasal Cavity Precision Medicine Female Adult Asthma Proteomics Cluster Analysis Unsupervised Machine Learning Benchmarking Microbiota Case-Control Studies Allergens Male Adolescent Epigenome Middle Aged Child, Preschool Datasets as Topic Gene Expression Profiling Child Gene Expression Regulation Transcriptome Feces Atlases as Topic
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High-dimensional profiling clusters asthma severity by lymphoid and non-lymphoid status.

Cell reports Apr 13, 2021
Clinical definitions of asthma fail to capture the heterogeneity of immune dysfunction in severe, treatment-refractory disease. Applying mass cytometry and machine learning to bronchoalveolar lavage (BAL) cells, we find that corticosteroid-resistant ...
Receptors, IgE Anti-Asthmatic Agents Adaptive Immunity Immunologic Memory Interleukin-7 Proteomics Signal Transduction Immunity, Innate CD8-Positive T-Lymphocytes CD4-Positive T-Lymphocytes Gene Expression Regulation Interferon-gamma Bronchoalveolar Lavage Fluid Adrenal Cortex Hormones Macrophages Asthma Humans Severity of Illness Index Machine Learning Gene Expression Profiling Interleukin-10 Case-Control Studies
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Single-cell analyses and machine learning define hematopoietic progenitor and HSC-like cells derived from human PSCs.

Blood Dec 17, 2020
Hematopoietic stem and progenitor cells (HSPCs) develop in distinct waves at various anatomical sites during embryonic development. The in vitro differentiation of human pluripotent stem cells (hPSCs) recapitulates some of these processes; however, i...
Fetus Pluripotent Stem Cells Hematopoietic Stem Cells Antigens, Differentiation Machine Learning Single-Cell Analysis RNA-Seq Liver Gene Expression Regulation Humans
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Predicting single-cell gene expression profiles of imaging flow cytometry data with machine learning.

Nucleic acids research Nov 18, 2020
High-content imaging and single-cell genomics are two of the most prominent high-throughput technologies for studying cellular properties and functions at scale. Recent studies have demonstrated that information in large imaging datasets can be used ...
Female Monocytes Single-Cell Analysis Gene Expression Regulation Databases, Genetic Animals Image Processing, Computer-Assisted Mice, Inbred C57BL Fetal Blood Male Mice Flow Cytometry Myeloid Progenitor Cells Gene Expression Profiling Computational Biology Humans High-Throughput Nucleotide Sequencing Transcriptome Neural Networks, Computer Machine Learning
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Fully interpretable deep learning model of transcriptional control.

Bioinformatics (Oxford, England) Jul 1, 2020
MOTIVATION: The universal expressibility assumption of Deep Neural Networks (DNNs) is the key motivation behind recent worksin the systems biology community to employDNNs to solve important problems in functional genomics and moleculargenetics. Typic...
Gene Expression Regulation Neural Networks, Computer Machine Learning Deep Learning Genomics
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Imputing missing RNA-sequencing data from DNA methylation by using a transfer learning-based neural network.

GigaScience Jul 1, 2020
BACKGROUND: Gene expression plays a key intermediate role in linking molecular features at the DNA level and phenotype. However, owing to various limitations in experiments, the RNA-seq data are missing in many samples while there exist high-quality ...
Gene Expression Regulation Prognosis Humans Epigenesis, Genetic Reproducibility of Results Neural Networks, Computer Epigenomics Neoplasms Machine Learning DNA Methylation Computational Biology Algorithms High-Throughput Nucleotide Sequencing CpG Islands
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