AIMC Topic: RNA, Neoplasm
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Improving platelet-RNA-based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification.
Molecular oncology
Jun 17, 2024
Liquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-lear...
Discriminating Neoplastic from Nonneoplastic Tissues Using an miRNA-Based Deep Cancer Classifier.
The American journal of pathology
Nov 10, 2021
Next-generation sequencing has enabled the collection of large biological data sets, allowing novel molecular-based classification methods to be developed for increased understanding of disease. miRNAs are small regulatory RNA molecules that can be q...
GATNNCDA: A Method Based on Graph Attention Network and Multi-Layer Neural Network for Predicting circRNA-Disease Associations.
International journal of molecular sciences
Aug 7, 2021
Circular RNAs (circRNAs) are a new class of endogenous non-coding RNAs with covalent closed loop structure. Researchers have revealed that circRNAs play an important role in human diseases. As experimental identification of interactions between circR...
Classification models for Invasive Ductal Carcinoma Progression, based on gene expression data-trained supervised machine learning.
Scientific reports
Mar 5, 2020
Early detection of breast cancer and its correct stage determination are important for prognosis and rendering appropriate personalized clinical treatment to breast cancer patients. However, despite considerable efforts and progress, there is a need ...
Carcinoma, Ductal, Breast
Microarray Analysis
Gene Ontology
RNA, Neoplasm
Models, Biological
Supervised Machine Learning
Datasets as Topic
Breast Neoplasms
Transcriptome
Protein Interaction Maps
Early Detection of Cancer
Neoplasm Staging
RNA-Seq
Databases, Genetic
Algorithms
Female
Reproducibility of Results
Humans
Machine Learning
DeepTRIAGE: interpretable and individualised biomarker scores using attention mechanism for the classification of breast cancer sub-types.
BMC medical genomics
Feb 24, 2020
BACKGROUND: Breast cancer is a collection of multiple tissue pathologies, each with a distinct molecular signature that correlates with patient prognosis and response to therapy. Accurately differentiating between breast cancer sub-types is an import...
Identifying Cancer-Specific circRNA-RBP Binding Sites Based on Deep Learning.
Molecules (Basel, Switzerland)
Nov 7, 2019
Circular RNAs (circRNAs) are extensively expressed in cells and tissues, and play crucial roles in human diseases and biological processes. Recent studies have reported that circRNAs could function as RNA binding protein (RBP) sponges, meanwhile RBPs...
Wx: a neural network-based feature selection algorithm for transcriptomic data.
Scientific reports
Jul 19, 2019
Next-generation sequencing (NGS), which allows the simultaneous sequencing of billions of DNA fragments simultaneously, has revolutionized how we study genomics and molecular biology by generating genome-wide molecular maps of molecules of interest. ...
Machine learning with the TCGA-HNSC dataset: improving usability by addressing inconsistency, sparsity, and high-dimensionality.
BMC bioinformatics
Jun 17, 2019
BACKGROUND: In the era of precision oncology and publicly available datasets, the amount of information available for each patient case has dramatically increased. From clinical variables and PET-CT radiomics measures to DNA-variant and RNA expressio...
Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm.
Computers in biology and medicine
May 3, 2019
Recent analysis identified distinct genomic subtypes of lower-grade glioma tumors which are associated with shape features. In this study, we propose a fully automatic way to quantify tumor imaging characteristics using deep learning-based segmentati...
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...
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