In the growing scenario, microarray data is extensively used since it provides a more comprehensive understanding of genetic variants among diseases. As the gene expression samples have high dimensionality it becomes tedious to analyze the samples ma...
IEEE/ACM transactions on computational biology and bioinformatics
29993693
To screen differentially expressed genes quickly and efficiently in breast cancer, two gene microarray datasets of breast cancer, GSE15852 and GSE45255, were downloaded from GEO. By combining the Logistic Regression and Random Forest algorithm, this ...
Methods based on microarrays (MA), mass spectrometry (MS), and machine learning (ML) algorithms have evolved rapidly in recent years, allowing for early detection of several types of cancer. A pitfall of these approaches, however, is the overfitting ...
Functional enrichment analysis is a fundamental and challenging task in bioinformatics. Most of the current enrichment analysis approaches individually evaluate functional terms and often output a list of enriched terms with high similarity and redun...
Journal of genetics and genomics = Yi chuan xue bao
30292791
Gene set enrichment (GSE) analyses play an important role in the interpretation of large-scale transcriptome datasets. Multiple GSE tools can be integrated into a single method as obtaining optimal results is challenging due to the plethora of GSE to...
In recent years DNA microarray technology, leading to the generation of high-volume biological data, has gained significant attention. To analyze this high volume gene-expression data, one such powerful tool is Clustering. For any clustering algorith...
Microarray technology is utilized by the biologists, in order to compute the expression levels of thousands of genes. Cervical cancer classification utilizing gene expression data depends upon conventional supervised learning methods, wherein only la...
At present, the study of gene expression data provides a reference for tumor diagnosis at the molecular level. It is a challenging task to select the feature genes related to the classification from the high-dimensional and small-sample gene expressi...
Microarrays are still one of the major techniques employed to study cancer biology. However, the identification of expression patterns from microarray datasets is still a significant challenge to overcome. In this work, a new approach using Neuroevol...