AIMC Topic:
Cluster Analysis
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Adaptive Fuzzy Consensus Clustering Framework for Clustering Analysis of Cancer Data.
IEEE/ACM transactions on computational biology and bioinformatics
Jan 1, 2015
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...
A New Semantic Functional Similarity over Gene Ontology.
IEEE/ACM transactions on computational biology and bioinformatics
Jan 1, 2015
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...
Acquiring Plausible Predications from MEDLINE by Clustering MeSH Annotations.
Studies in health technology and informatics
Jan 1, 2015
The massive accumulation of biomedical knowledge is reflected by the growth of the literature database MEDLINE with over 23 million bibliographic records. All records are manually indexed by MeSH descriptors, many of them refined by MeSH subheadings....
Optimizing artificial neural network models for metabolomics and systems biology: an example using HPLC retention index data.
Bioanalysis
Jan 1, 2015
BACKGROUND: Artificial Neural Networks (ANN) are extensively used to model 'omics' data. Different modeling methodologies and combinations of adjustable parameters influence model performance and complicate model optimization.
Adaptive neuro-fuzzy inference system for real-time monitoring of integrated-constructed wetlands.
Water science and technology : a journal of the International Association on Water Pollution Research
Jan 1, 2015
Monitoring large-scale treatment wetlands is costly and time-consuming, but required by regulators. Some analytical results are available only after 5 days or even longer. Thus, adaptive neuro-fuzzy inference system (ANFIS) models were developed to p...
Neural networks and Fuzzy clustering methods for assessing the efficacy of microarray based intrinsic gene signatures in breast cancer classification and the character and relations of identified subtypes.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2015
In the classification of breast cancer subtypes using microarray data, hierarchical clustering is commonly used. Although this form of clustering shows basic cluster patterns, more needs to be done to investigate the accuracy of clusters as well as t...
Performance analysis of unsupervised optimal fuzzy clustering algorithm for MRI brain tumor segmentation.
Technology and health care : official journal of the European Society for Engineering and Medicine
Jan 1, 2015
BACKGROUND: Segmentation of brain tumor from Magnetic Resonance Imaging (MRI) becomes very complicated due to the structural complexities of human brain and the presence of intensity inhomogeneities.
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