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Gene Expression Regulation, Neoplastic

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Identification of the functional alteration signatures across different cancer types with support vector machine and feature analysis.

Biochimica et biophysica acta. Molecular basis of disease
Cancers are regarded as malignant proliferations of tumor cells present in many tissues and organs, which can severely curtail the quality of human life. The potential of using plasma DNA for cancer detection has been widely recognized, leading to th...

Hybrid Method Based on Information Gain and Support Vector Machine for Gene Selection in Cancer Classification.

Genomics, proteomics & bioinformatics
It remains a great challenge to achieve sufficient cancer classification accuracy with the entire set of genes, due to the high dimensions, small sample size, and big noise of gene expression data. We thus proposed a hybrid gene selection method, Inf...

Construction of a 26‑feature gene support vector machine classifier for smoking and non‑smoking lung adenocarcinoma sample classification.

Molecular medicine reports
The present study aimed to identify the feature genes associated with smoking in lung adenocarcinoma (LAC) samples and explore the underlying mechanism. Three gene expression datasets of LAC samples were downloaded from the Gene Expression Omnibus da...

A novel machine learning approach reveals latent vascular phenotypes predictive of renal cancer outcome.

Scientific reports
Gene expression signatures are commonly used as predictive biomarkers, but do not capture structural features within the tissue architecture. Here we apply a 2-step machine learning framework for quantitative imaging of tumor vasculature to derive a ...

Unsupervised deep learning reveals prognostically relevant subtypes of glioblastoma.

BMC bioinformatics
BACKGROUND: One approach to improving the personalized treatment of cancer is to understand the cellular signaling transduction pathways that cause cancer at the level of the individual patient. In this study, we used unsupervised deep learning to le...

A support vector machine classifier for the prediction of osteosarcoma metastasis with high accuracy.

International journal of molecular medicine
In this study, gene expression profiles of osteosarcoma (OS) were analyzed to identify critical genes associated with metastasis. Five gene expression datasets were screened and downloaded from Gene Expression Omnibus (GEO). Following assessment by M...

Expression of AdipoR1 and AdipoR2 Receptors as Leptin-Breast Cancer Regulation Mechanisms.

Disease markers
The development of breast cancer is influenced by the adipose tissue through the proteins leptin and adiponectin. However, there is little research concerning AdipoR1 and AdipoR2 receptors and the influence of leptin over them. The objective of this ...

Finding disagreement pathway signatures and constructing an ensemble model for cancer classification.

Scientific reports
Cancer classification based on molecular level is a relatively routine research procedure with advances in high-throughput molecular profiling techniques. However, the number of genes typically far exceeds the number of the sample size in gene expres...