AI Medical Compendium Topic:
Databases, Genetic

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A novel random forests-based feature selection method for microarray expression data analysis.

International journal of data mining and bioinformatics
High-dimensional data and a large number of redundancy features in bioinformatics research have created an urgent need for feature selection. In this paper, a novel random forests-based feature selection method is proposed that adopts the idea of str...

Gene function prediction with knowledge from gene ontology.

International journal of data mining and bioinformatics
Gene function prediction is an important problem in bioinformatics. Due to the inherent noise existing in the gene expression data, the attempt to improve the prediction accuracy resorting to new classification techniques is limited. With the emergen...

Ensemble of sparse classifiers for high-dimensional biological data.

International journal of data mining and bioinformatics
Biological data are often high in dimension while the number of samples is small. In such cases, the performance of classification can be improved by reducing the dimension of data, which is referred to as feature selection. Recently, a novel feature...

Employing social network analysis for disease biomarker detection.

International journal of data mining and bioinformatics
Detection of disease biomarkers in general and cancer biomarkers in particular is an important task which has received considerable attention in the area of in silico genomic experiments. We describe a new approach for detecting cancer biomarkers bas...

Regularised extreme learning machine with misclassification cost and rejection cost for gene expression data classification.

International journal of data mining and bioinformatics
The main purpose of traditional classification algorithms on bioinformatics application is to acquire better classification accuracy. However, these algorithms cannot meet the requirement that minimises the average misclassification cost. In this pap...

Classification of imbalanced bioinformatics data by using boundary movement-based ELM.

Bio-medical materials and engineering
To address the imbalanced classification problem emerging in Bioinformatics, a boundary movement-based extreme learning machine (ELM) algorithm called BM-ELM was proposed. BM-ELM tries to firstly explore the prior information about data distribution ...

Adaptive Fuzzy Consensus Clustering Framework for Clustering Analysis of Cancer Data.

IEEE/ACM transactions on computational biology and bioinformatics
Performing clustering analysis is one of the important research topics in cancer discovery using gene expression profiles, which is crucial in facilitating the successful diagnosis and treatment of cancer. While there are quite a number of research w...

Supervised Variational Relevance Learning, An Analytic Geometric Feature Selection with Applications to Omic Datasets.

IEEE/ACM transactions on computational biology and bioinformatics
We introduce Supervised Variational Relevance Learning (Suvrel), a variational method to determine metric tensors to define distance based similarity in pattern classification, inspired in relevance learning. The variational method is applied to a co...

A New Semantic Functional Similarity over Gene Ontology.

IEEE/ACM transactions on computational biology and bioinformatics
Identifying functionally similar or closely related genes and gene products has significant impacts on biological and clinical studies as well as drug discovery. In this paper, we propose an effective and practically useful method measuring both gene...

Named entity recognition and classification in biomedical text using classifier ensemble.

International journal of data mining and bioinformatics
Named Entity Recognition and Classification (NERC) is an important task in information extraction for biomedicine domain. Biomedical Named Entities include mentions of proteins, genes, DNA, RNA, etc. which, in general, have complex structures and are...