AIMC Topic: Genes, Neoplasm

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Applications of Support Vector Machine (SVM) Learning in Cancer Genomics.

Cancer genomics & proteomics Jan 1, 2018
Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in h...
Humans Biomarkers, Tumor Neoplasms Drug Discovery Genomics Support Vector Machine Protein Interaction Mapping Genes, Neoplasm
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A hierarchical two-phase framework for selecting genes in cancer datasets with a neuro-fuzzy system.

Technology and health care : official journal of the European Society for Engineering and Medicine Apr 29, 2016
Finding the minimum number of appropriate biomarkers for specific targets such as a lung cancer has been a challenging issue in bioinformatics. We propose a hierarchical two-phase framework for selecting appropriate biomarkers that extracts candidate...
Fuzzy Logic Datasets as Topic Microarray Analysis Decision Making, Computer-Assisted Genes, Neoplasm Choice Behavior
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Structural Comparison of Gene Relevance Networks for Breast Cancer Tissues in Different Grades.

Combinatorial chemistry & high throughput screening Jan 1, 2016
BACKGROUND: The breast is an important biological system of human with two distinct states, i.e. normal and tumoral. Research on breast cancer could be based on systematic modeling to contrast the system structures of these two states.
Humans Female Breast Neoplasms Gene Regulatory Networks Support Vector Machine Lipocalin-2 ErbB Receptors ras Proteins Genes, Neoplasm Proto-Oncogene Proteins c-fos ZAP-70 Protein-Tyrosine Kinase bcl-2 Homologous Antagonist-Killer Protein
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Identification of hepatocellular carcinoma-related genes with a machine learning and network analysis.

Journal of computational biology : a journal of computational molecular cell biology Jan 1, 2015
Liver cancer is one of the leading causes of cancer mortality worldwide. Hepatocellular carcinoma (HCC) is the main type of liver cancer. We applied a machine learning approach with maximum-relevance-minimum-redundancy (mRMR) algorithm followed by in...
Humans Artificial Intelligence Liver Neoplasms Carcinoma, Hepatocellular Gene Regulatory Networks Models, Genetic Databases, Genetic Gene Ontology Genes, Neoplasm
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