AIMC Topic: Gene Expression Regulation

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Using neural networks for reducing the dimensions of single-cell RNA-Seq data.

Nucleic acids research Sep 29, 2017
While only recently developed, the ability to profile expression data in single cells (scRNA-Seq) has already led to several important studies and findings. However, this technology has also raised several new computational challenges. These include ...
Datasets as Topic Gene Expression Regulation Protein Interaction Mapping Multifactor Dimensionality Reduction Databases, Genetic Cluster Analysis RNA Humans Neural Networks, Computer Software Gene Expression Profiling Single-Cell Analysis Computational Biology Sequence Analysis, RNA
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An efficient graph kernel method for non-coding RNA functional prediction.

Bioinformatics (Oxford, England) Sep 1, 2017
MOTIVATION: The importance of RNA protein-coding gene regulation is by now well appreciated. Non-coding RNAs (ncRNAs) are known to regulate gene expression at practically every stage, ranging from chromatin packaging to mRNA translation. However the ...
Supervised Machine Learning Gene Expression Regulation Molecular Sequence Annotation RNA, Untranslated Humans Software Computational Biology Sequence Analysis, RNA
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A deep boosting based approach for capturing the sequence binding preferences of RNA-binding proteins from high-throughput CLIP-seq data.

Nucleic acids research Aug 21, 2017
Characterizing the binding behaviors of RNA-binding proteins (RBPs) is important for understanding their functional roles in gene expression regulation. However, current high-throughput experimental methods for identifying RBP targets, such as CLIP-s...
Protein Binding Computational Biology RNA-Binding Proteins Mutation Machine Learning Algorithms Reproducibility of Results Binding Sites Nucleotide Motifs Binding, Competitive 3' Untranslated Regions Internet High-Throughput Nucleotide Sequencing Gene Expression Regulation Base Sequence Humans
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Machine learning in computational biology to accelerate high-throughput protein expression.

Bioinformatics (Oxford, England) Aug 15, 2017
MOTIVATION: The Human Protein Atlas (HPA) enables the simultaneous characterization of thousands of proteins across various tissues to pinpoint their spatial location in the human body. This has been achieved through transcriptomics and high-throughp...
Organ Specificity Humans Proteome Machine Learning Escherichia coli Computational Biology Solubility Gene Expression Regulation
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Machine Learning Techniques in Exploring MicroRNA Gene Discovery, Targets, and Functions.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2017
In recent years, the role of miRNAs in post-transcriptional gene regulation has provided new insights into the understanding of several types of cancers and neurological disorders. Although miRNA research has gathered great momentum since its discove...
Animals Gene Regulatory Networks Genomics RNA, Messenger MicroRNAs Data Mining Gene Expression Regulation Humans Machine Learning
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Exploring Genome-Wide Expression Profiles Using Machine Learning Techniques.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2017
Although contemporary high-throughput -omics methods produce high-dimensional data, the resulting wealth of information is difficult to assess using traditional statistical procedures. Machine learning methods facilitate the detection of additional p...
Genomics Computational Biology Cluster Analysis Periodontitis Periodontal Diseases Gene Expression Regulation Phenotype Gene Expression Profiling Transcriptome Genome-Wide Association Study Machine Learning Software Algorithms Humans
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Effect of doxycycline on transforming growth factor-beta-1-induced matrix metalloproteinase 2 expression, migration, and collagen contraction in nasal polyp-derived fibroblasts.

American journal of rhinology & allergy Nov 1, 2016
PURPOSE: It is well known that doxycycline has antibacterial and anti-inflammatory effects. In this study, we aimed to investigate the effects of doxycycline on the transforming growth factor (TGF) beta 1-induced matrix metalloproteinase (MMP) 2 expr...
Cell Movement Fibroblasts Gene Expression Regulation Humans Cell Differentiation Young Adult Doxycycline Cells, Cultured Nasal Polyps Transforming Growth Factor beta1 Adult Female Smad2 Protein Matrix Metalloproteinase 2 Male Collagen Signal Transduction
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DeepChrome: deep-learning for predicting gene expression from histone modifications.

Bioinformatics (Oxford, England) Sep 1, 2016
MOTIVATION: Histone modifications are among the most important factors that control gene regulation. Computational methods that predict gene expression from histone modification signals are highly desirable for understanding their combinatorial effec...
Humans Neural Networks, Computer Gene Regulatory Networks Computational Biology Gene Expression Regulation Epigenesis, Genetic Histone Code Support Vector Machine Cluster Analysis
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Preface.

Journal of biosciences Oct 1, 2015
Humans Machine Learning Gene Regulatory Networks Computational Biology Pattern Recognition, Automated Gene Expression Regulation Signal Transduction Microarray Analysis Multifactor Dimensionality Reduction Plants Data Mining High-Throughput Nucleotide Sequencing
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Mining Gene Regulatory Networks by Neural Modeling of Expression Time-Series.

IEEE/ACM transactions on computational biology and bioinformatics Jan 1, 2015
Discovering gene regulatory networks from data is one of the most studied topics in recent years. Neural networks can be successfully used to infer an underlying gene network by modeling expression profiles as times series. This work proposes a novel...
Data Mining Pattern Recognition, Automated Gene Expression Regulation Animals Gene Expression Profiling Proteome Humans Signal Transduction Neural Networks, Computer Algorithms
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