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Gene Expression Regulation, Neoplastic

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Screening of disorders associated with osteosarcoma by integrated network analysis.

Bioscience reports
Osteosarcoma is a common malignant bone tumor in children and adolescents under the age of 20. However, research on the pathogenesis and treatment of osteosarcoma is still insufficient. In the present study, based on gene-phenotype correlation networ...

Attention-Based Multi-NMF Deep Neural Network with Multimodality Data for Breast Cancer Prognosis Model.

BioMed research international
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...

Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm.

Computers in biology and medicine
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...

Analysis of Expression Pattern of snoRNAs in Different Cancer Types with Machine Learning Algorithms.

International journal of molecular sciences
Small nucleolar RNAs (snoRNAs) are a new type of functional small RNAs involved in the chemical modifications of rRNAs, tRNAs, and small nuclear RNAs. It is reported that they play important roles in tumorigenesis via various regulatory modes. snoRNA...

Multilayer network analysis of miRNA and protein expression profiles in breast cancer patients.

PloS one
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...

Prediction of molecular subtypes of breast cancer using BI-RADS features based on a "white box" machine learning approach in a multi-modal imaging setting.

European journal of radiology
PURPOSE: To develop and validate an interpretable and repeatable machine learning model approach to predict molecular subtypes of breast cancer from clinical metainformation together with mammography and MRI images.

Model based on GA and DNN for prediction of mRNA-Smad7 expression regulated by miRNAs in breast cancer.

Theoretical biology & medical modelling
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...

Integrative Gene Selection on Gene Expression Data: Providing Biological Context to Traditional Approaches.

Journal of integrative bioinformatics
The advance of high-throughput RNA-Sequencing techniques enables researchers to analyze the complete gene activity in particular cells. From the insights of such analyses, researchers can identify disease-specific expression profiles, thus understand...