AIMC Topic: Gene Expression Profiling

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Statistical characterization and classification of colon microarray gene expression data using multiple machine learning paradigms.

Computer methods and programs in biomedicine Apr 10, 2019
OBJECTIVE: A colon microarray data is a repository of thousands of gene expressions with different strengths for each cancer cell. It is necessary to detect which genes are responsible for cancer growth. This study presents an exhaustive comparative ...
Colonic Neoplasms Risk Neural Networks, Computer Normal Distribution Oncogenes Machine Learning Tissue Array Analysis Humans Sensitivity and Specificity Decision Trees Colon Area Under Curve Support Vector Machine Bayes Theorem Models, Statistical Discriminant Analysis Regression Analysis Gene Expression Profiling Logistic Models
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Identification of Hürthle cell cancers: solving a clinical challenge with genomic sequencing and a trio of machine learning algorithms.

BMC systems biology Apr 5, 2019
BACKGROUND: Identification of Hürthle cell cancers by non-operative fine-needle aspiration biopsy (FNAB) of thyroid nodules is challenging. Resultingly, non-cancerous Hürthle lesions were conventionally distinguished from Hürthle cell cancers by hist...
Genomics Mitochondria Heterozygote Sequence Analysis Oxyphil Cells Humans Machine Learning Neoplasms Gene Expression Profiling
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Multilayer network analysis of miRNA and protein expression profiles in breast cancer patients.

PloS one Apr 4, 2019
MiRNAs and proteins play important roles in different stages of breast tumor development and serve as biomarkers for the early diagnosis of breast cancer. A new algorithm that combines machine learning algorithms and multilayer complex network analys...
Neoplasm Proteins Gene Expression Profiling RNA, Neoplasm Gene Regulatory Networks Gene Expression Regulation, Neoplastic MicroRNAs Humans Machine Learning Female Breast Neoplasms
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Deep-learning augmented RNA-seq analysis of transcript splicing.

Nature methods Mar 25, 2019
A major limitation of RNA sequencing (RNA-seq) analysis of alternative splicing is its reliance on high sequencing coverage. We report DARTS (https://github.com/Xinglab/DARTS), a computational framework that integrates deep-learning-based predictions...
RNA High-Throughput Nucleotide Sequencing Gene Expression Regulation K562 Cells Hep G2 Cells Models, Statistical Bayes Theorem Signal Processing, Computer-Assisted Humans RNA Splicing Algorithms Exons Deep Learning Alternative Splicing Sequence Analysis, RNA Epigenomics Reproducibility of Results Gene Expression Profiling
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Group Lasso Regularized Deep Learning for Cancer Prognosis from Multi-Omics and Clinical Features.

Genes Mar 21, 2019
Accurate prognosis of patients with cancer is important for the stratification of patients, the optimization of treatment strategies, and the design of clinical trials. Both clinical features and molecular data can be used for this purpose, for insta...
Computational Biology DNA Methylation Prognosis Neoplasms Gene Expression Profiling Deep Learning Genomics Humans
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Gene Expression Classification of Lung Adenocarcinoma into Molecular Subtypes.

IEEE/ACM transactions on computational biology and bioinformatics Mar 18, 2019
As one of the most common malignancies in the world, lung adenocarcinoma (LUAD) is currently difficult to cure. However, the advent of precision medicine provides an opportunity to improve the treatment of lung cancer. Subtyping lung cancer plays an ...
Lung Neoplasms Cluster Analysis Mutation Adenocarcinoma of Lung Algorithms Biomarkers, Tumor Gene Expression Profiling Transcriptome Humans Neural Networks, Computer
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Scalable analysis of cell-type composition from single-cell transcriptomics using deep recurrent learning.

Nature methods Mar 18, 2019
Recent advances in large-scale single-cell RNA-seq enable fine-grained characterization of phenotypically distinct cellular states in heterogeneous tissues. We present scScope, a scalable deep-learning-based approach that can accurately and rapidly i...
Phenotype Computer Simulation Reproducibility of Results Sequence Analysis, RNA Software Algorithms Intestines Inflammation Databases, Genetic Deep Learning Principal Component Analysis Single-Cell Analysis Retina Mice RNA Computational Biology Cluster Analysis Animals Brain Mapping Leukocytes, Mononuclear Gene Expression Profiling Transcriptome
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Machine learning applied to transcriptomic data to identify genes associated with feed efficiency in pigs.

Genetics, selection, evolution : GSE Mar 13, 2019
BACKGROUND: To date, the molecular mechanisms that underlie residual feed intake (RFI) in pigs are unknown. Results from different genome-wide association studies and gene expression analyses are not always consistent. The aim of this research was to...
Animal Nutritional Physiological Phenomena Breeding Swine Gene Expression Profiling Transcriptome Animal Feed Machine Learning Animals
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Artificial intelligence based discovery of the association between depression and chronic fatigue syndrome.

Journal of affective disorders Mar 8, 2019
BACKGROUND: Both of the modern medicine and the traditional Chinese medicine classify depressive disorder (DD) and chronic fatigue syndrome (CFS) to one type of disease. Unveiling the association between depressive and the fatigue diseases provides a...
Depressive Disorder, Major Gene Expression Profiling Metabolomics Principal Component Analysis Depressive Disorder Least-Squares Analysis Magnetic Resonance Spectroscopy Female Adult Male Middle Aged Humans Artificial Intelligence Fatigue Syndrome, Chronic Biomarkers
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Identification of esophageal cancer pathway deviation and construction of a diagnosis model using three kernel genes.

Journal of cellular physiology Mar 5, 2019
The purpose of this study is to better understand the role of interleukin 35 (IL35) in esophageal carcinoma by comparing the mRNA level in Barrett's esophageal mucosa and in matched normal squamous mucosa and to understand how the diagnosis model wor...
Humans Reproducibility of Results Deep Learning Gene Expression Regulation, Neoplastic Models, Genetic Databases, Genetic Early Detection of Cancer Biomarkers, Tumor Gene Expression Profiling Transcriptome Case-Control Studies Esophageal Squamous Cell Carcinoma Hepatocyte Nuclear Factor 1-beta Interleukin-12 Subunit p35 Nerve Tissue Proteins Predictive Value of Tests Esophageal Neoplasms Cyclic AMP Response Element-Binding Protein
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