AIMC Topic: Databases, Genetic

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The feature selection bias problem in relation to high-dimensional gene data.

Artificial intelligence in medicine
OBJECTIVE: Feature selection is a technique widely used in data mining. The aim is to select the best subset of features relevant to the problem being considered. In this paper, we consider feature selection for the classification of gene datasets. G...

Gene and sample selection using T-score with sample selection.

Journal of biomedical informatics
Gene selection from high-dimensional microarray gene-expression data is statistically a challenging problem. Filter approaches to gene selection have been popular because of their simplicity, efficiency, and accuracy. Due to small sample size, all sa...

Ontology-Based Search of Genomic Metadata.

IEEE/ACM transactions on computational biology and bioinformatics
The Encyclopedia of DNA Elements (ENCODE) is a huge and still expanding public repository of more than 4,000 experiments and 25,000 data files, assembled by a large international consortium since 2007; unknown biological knowledge can be extracted fr...

Survey of Natural Language Processing Techniques in Bioinformatics.

Computational and mathematical methods in medicine
Informatics methods, such as text mining and natural language processing, are always involved in bioinformatics research. In this study, we discuss text mining and natural language processing methods in bioinformatics from two perspectives. First, we...

PDON: Parkinson's disease ontology for representation and modeling of the Parkinson's disease knowledge domain.

Theoretical biology & medical modelling
BACKGROUND: Despite the unprecedented and increasing amount of data, relatively little progress has been made in molecular characterization of mechanisms underlying Parkinson's disease. In the area of Parkinson's research, there is a pressing need to...

A Framework for Identifying Genotypic Information from Clinical Records: Exploiting Integrated Ontology Structures to Transfer Annotations between ICD Codes and Gene Ontologies.

IEEE/ACM transactions on computational biology and bioinformatics
Although some methods are proposed for automatic ontology generation, none of them address the issue of integrating large-scale heterogeneous biomedical ontologies. We propose a novel approach for integrating various types of ontologies efficiently a...

Supervised, Unsupervised, and Semi-Supervised Feature Selection: A Review on Gene Selection.

IEEE/ACM transactions on computational biology and bioinformatics
Recently, feature selection and dimensionality reduction have become fundamental tools for many data mining tasks, especially for processing high-dimensional data such as gene expression microarray data. Gene expression microarray data comprises up t...

An empirical study of ensemble-based semi-supervised learning approaches for imbalanced splice site datasets.

BMC systems biology
BACKGROUND: Recent biochemical advances have led to inexpensive, time-efficient production of massive volumes of raw genomic data. Traditional machine learning approaches to genome annotation typically rely on large amounts of labeled data. The proce...

PPDB: A Tool for Investigation of Plants Physiology Based on Gene Ontology.

Interdisciplinary sciences, computational life sciences
Representing the way forward, from functional genomics and its ontology to functional understanding and physiological model, in a computationally tractable fashion is one of the ongoing challenges faced by computational biology. To tackle the standpo...