AIMC Topic: RNA, Messenger

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Classifying Breast Cancer Subtypes Using Multiple Kernel Learning Based on Omics Data.

Genes Mar 7, 2019
It is very significant to explore the intrinsic differences in breast cancer subtypes. These intrinsic differences are closely related to clinical diagnosis and designation of treatment plans. With the accumulation of biological and medicine datasets...
Machine Learning Female Genomics Humans DNA Copy Number Variations Receptor, ErbB-2 Receptors, Estrogen Receptors, Progesterone RNA, Messenger Triple Negative Breast Neoplasms DNA Methylation
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Significant improvement of miRNA target prediction accuracy in large datasets using meta-strategy based on comprehensive voting and artificial neural networks.

BMC genomics Feb 27, 2019
BACKGROUND: Identifying mRNA targets of miRNAs is critical for studying gene expression regulation at the whole-genome level. Multiple computational tools have been developed to predict miRNA:mRNA interactions. Nonetheless, many of these tools are de...
Datasets as Topic Gene Expression Regulation RNA, Messenger MicroRNAs Neural Networks, Computer
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Discovering functional impacts of miRNAs in cancers using a causal deep learning model.

BMC medical genomics Dec 31, 2018
BACKGROUND: Micro-RNAs (miRNAs) play a significant role in regulating gene expression under physiological and pathological conditions such as cancers. However, it remains a challenging problem to discover the target messenger RNAs (mRNAs) of a miRNA ...
Humans Neoplasms MicroRNAs Models, Statistical RNA, Neoplasm Deep Learning RNA, Messenger Models, Genetic
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Model based on GA and DNN for prediction of mRNA-Smad7 expression regulated by miRNAs in breast cancer.

Theoretical biology & medical modelling Dec 29, 2018
BACKGROUND: The Smad7 protein is negative regulator of the TGF-β signaling pathway, which is upregulated in patients with breast cancer. miRNAs regulate proteins expressions by arresting or degrading the mRNAs. The purpose of this work is to identify...
Humans Gene Expression Regulation, Neoplastic MicroRNAs Models, Biological Smad7 Protein Neural Networks, Computer Breast Neoplasms Algorithms Deep Learning Female RNA, Messenger
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In vitro intestinal epithelium responses to titanium dioxide nanoparticles.

Food research international (Ottawa, Ont.) Oct 12, 2018
Titanium dioxide (TiO) is enclosed in many consumer products including pharmaceuticals, cosmetics, and foods. TiO (E171) is daily ingested as mixed nano- and submicron-sized particles since it is approved as a white colorant in Europe in a wide varie...
Caco-2 Cells RNA, Messenger Humans Titanium Intestinal Mucosa Tumor Necrosis Factor-alpha Endoplasmic Reticulum Stress Cytokines Food Additives Interleukin-8 Nanoparticles Particle Size
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SiRNA silencing efficacy prediction based on a deep architecture.

BMC genomics Sep 24, 2018
BACKGROUND: Small interfering RNA (siRNA) can be used to post-transcriptional gene regulation by knocking down targeted genes. In functional genomics, biomedical research and cancer therapeutics, siRNA design is a critical research topic. Various com...
Gene Silencing RNA, Messenger RNA, Small Interfering Gene Targeting Humans Neural Networks, Computer Machine Learning Algorithms Computational Biology
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Machine learning approaches infer vitamin D signaling: Critical impact of vitamin D receptor binding within topologically associated domains.

The Journal of steroid biochemistry and molecular biology Jul 22, 2018
The vitamin D-modulated transcriptome of highly responsive human cells, such as THP-1 monocytes, comprises more than 500 genes, half of which are primary targets. Recently, we proposed a chromatin model of vitamin D signaling demonstrating that nearl...
High-Throughput Nucleotide Sequencing Gene Expression Regulation Chromatin CCCTC-Binding Factor Humans Receptors, Calcitriol Machine Learning Algorithms Cell Line Protein Binding RNA, Messenger THP-1 Cells Signal Transduction Vitamin D
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A Supervised Ensemble Approach for Sensitive microRNA Target Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Jul 20, 2018
MicroRNAs, a class of small non-coding RNAs, regulate important biological functions via post-transcriptional regulation of messenger RNAs (mRNAs). Despite rapid development in miRNA research, precise experimental methods to determine miRNA target in...
Humans Algorithms Gene Expression Regulation MicroRNAs Supervised Machine Learning Computational Biology HEK293 Cells RNA, Messenger Sequence Analysis, RNA
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miRAW: A deep learning-based approach to predict microRNA targets by analyzing whole microRNA transcripts.

PLoS computational biology Jul 13, 2018
MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression by binding to partially complementary regions within the 3'UTR of their target genes. Computational methods play an important role in target prediction and assume that the miR...
3' Untranslated Regions Binding Sites Thermodynamics Gene Targeting MicroRNAs Datasets as Topic Gene Expression Regulation Humans Neural Networks, Computer Deep Learning RNA, Messenger Computer Simulation Reproducibility of Results
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Tiresias: Context-sensitive Approach to Decipher the Presence and Strength of MicroRNA Regulatory Interactions.

Theranostics Jan 1, 2018
MicroRNAs (miRNAs) are short non-coding RNAs that regulate expression of target messenger RNAs (mRNAs) post-transcriptionally. Understanding the precise regulatory role of miRNAs is of great interest since miRNAs have been shown to play an important ...
Animals Computational Biology RNA, Messenger Humans Neural Networks, Computer Machine Learning Gene Expression Regulation, Neoplastic MicroRNAs Bayes Theorem
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