AIMC Topic: Transcriptome

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Type-2 Fuzzy PCA Approach in Extracting Salient Features for Molecular Cancer Diagnostics and Prognostics.

IEEE transactions on nanobioscience May 20, 2019
Machine learning is becoming a powerful tool for cancer diagnosis and prognosis based on classification using high dimensional molecular data. However, extracting classification features from high-dimensional datasets remains a challenging problem. P...
Humans Transcriptome Computational Biology Databases, Genetic Fuzzy Logic Principal Component Analysis Machine Learning Prognosis Neoplasms Gene Expression Profiling
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Attention-Based Multi-NMF Deep Neural Network with Multimodality Data for Breast Cancer Prognosis Model.

BioMed research international May 13, 2019
Today, it has become a hot issue in cancer research to make precise prognostic prediction for breast cancer patients, which can not only effectively avoid overtreatment and medical resources waste, but also provide scientific basis to help medical st...
Databases, Nucleic Acid Breast Neoplasms Humans Neural Networks, Computer Gene Expression Profiling Algorithms Transcriptome Female Gene Expression Regulation, Neoplastic
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Machine-learning based radiogenomics analysis of MRI features and metagenes in glioblastoma multiforme patients with different survival time.

Journal of cellular and molecular medicine Apr 18, 2019
BACKGROUND: This study aimed to examine multi-dimensional MRI features' predictability on survival outcome and associations with differentially expressed Genes (RNA Sequencing) in groups of glioblastoma multiforme (GBM) patients.
Young Adult Adult Survival Rate Biomarkers, Tumor Prognosis Female Aged Aged, 80 and over Transcriptome Adolescent ROC Curve Genomics Gene Expression Regulation, Neoplastic Brain Neoplasms Male Middle Aged Gene Expression Profiling Humans Machine Learning Algorithms Magnetic Resonance Imaging Glioblastoma Radiographic Image Interpretation, Computer-Assisted
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A directed learning strategy integrating multiple omic data improves genomic prediction.

Plant biotechnology journal Apr 14, 2019
Genomic prediction (GP) aims to construct a statistical model for predicting phenotypes using genome-wide markers and is a promising strategy for accelerating molecular plant breeding. However, current progress of phenotype prediction using genomic d...
Oryza Genetic Markers Supervised Machine Learning Quantitative Trait Loci Polymorphism, Single Nucleotide Phenotype Models, Genetic Transcriptome Models, Statistical Genomics Metabolome
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Capsule Network Based Modeling of Multi-omics Data for Discovery of Breast Cancer-Related Genes.

IEEE/ACM transactions on computational biology and bioinformatics Apr 9, 2019
Breast cancer is one of the most common cancers all over the world, which bring about more than 450,000 deaths each year. Although this malignancy has been extensively studied by a large number of researchers, its prognosis is still poor. Since thera...
Transcriptome Deep Learning Computational Biology DNA Methylation Prognosis DNA Copy Number Variations Humans Female Genes, Neoplasm Breast Neoplasms Biomarkers, Tumor
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Application of a Neural Network Whole Transcriptome-Based Pan-Cancer Method for Diagnosis of Primary and Metastatic Cancers.

JAMA network open Apr 5, 2019
IMPORTANCE: A molecular diagnostic method that incorporates information about the transcriptional status of all genes across multiple tissue types can strengthen confidence in cancer diagnosis.
Neoplasms Transcriptome Lung Neoplasms Mesothelioma Biomarkers, Tumor Mesothelioma, Malignant Humans Cross-Sectional Studies Exome Sequencing Male Neural Networks, Computer Middle Aged Machine Learning Female Adult
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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 ...
Humans Mutation Neural Networks, Computer Adenocarcinoma of Lung Transcriptome Algorithms Biomarkers, Tumor Lung Neoplasms Gene Expression Profiling Cluster Analysis
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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 Principal Component Analysis Animals Leukocytes, Mononuclear Retina Single-Cell Analysis Software Gene Expression Profiling Inflammation Computational Biology Mice RNA Algorithms Databases, Genetic Transcriptome Deep Learning Cluster Analysis Sequence Analysis, RNA Brain Mapping Intestines
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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...
Animals Swine Gene Expression Profiling Transcriptome Breeding Animal Feed Animal Nutritional Physiological Phenomena Machine Learning
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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 Early Detection of Cancer Nerve Tissue Proteins Predictive Value of Tests Biomarkers, Tumor Cyclic AMP Response Element-Binding Protein Deep Learning Hepatocyte Nuclear Factor 1-beta Esophageal Neoplasms Gene Expression Profiling Esophageal Squamous Cell Carcinoma Gene Expression Regulation, Neoplastic Interleukin-12 Subunit p35 Transcriptome Models, Genetic Case-Control Studies Databases, Genetic
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