AIMC Topic:
Cluster Analysis
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A multitask multiple kernel learning formulation for discriminating early- and late-stage cancers.
Bioinformatics (Oxford, England)
Jun 1, 2020
MOTIVATION: Genomic information is increasingly being used in diagnosis, prognosis and treatment of cancer. The severity of the disease is usually measured by the tumor stage. Therefore, identifying pathways playing an important role in progression o...
GSOAP: a tool for visualization of gene set over-representation analysis.
Bioinformatics (Oxford, England)
May 1, 2020
MOTIVATION: Gene sets over-representation analysis (GSOA) is a common technique of enrichment analysis that measures the overlap between a gene set and selected instances (e.g. pathways). Despite its popularity, there is currently no established stan...
Deep-learning approach to identifying cancer subtypes using high-dimensional genomic data.
Bioinformatics (Oxford, England)
Mar 1, 2020
MOTIVATION: Cancer subtype classification has the potential to significantly improve disease prognosis and develop individualized patient management. Existing methods are limited by their ability to handle extremely high-dimensional data and by the i...
Antibody Clustering Using a Machine Learning Pipeline that Fuses Genetic, Structural, and Physicochemical Properties.
Advances in experimental medicine and biology
Jan 1, 2020
Antibody V domain clustering is of paramount importance to a repertoire of immunology-related areas. Although several approaches have been proposed for antibody clustering, still no consensus has been reached. Numerous attempts use information from g...
An Improved B-hill Climbing Optimization Technique for Solving the Text Documents Clustering Problem.
Current medical imaging
Jan 1, 2020
BACKGROUND: Considering the increasing volume of text document information on Internet pages, dealing with such a tremendous amount of knowledge becomes totally complex due to its large size. Text clustering is a common optimization problem used to m...
Detecting anomalous growth of skin lesion using threshold-based segmentation algorithm and Fuzzy K-Nearest Neighbor classifier.
Journal of cancer research and therapeutics
Jan 1, 2020
CONTEXT: Skin cancer is a complex and life-threatening disease caused primarily by genetic instability and accumulation of multiple molecular alternations.
Diastolic Function Evaluation: What Can We Learn From Machine Learning?
JACC. Cardiovascular imaging
Jan 1, 2020
Fuzzy Gaussian Lasso clustering with application to cancer data.
Mathematical biosciences and engineering : MBE
Sep 30, 2019
Recently, Yang et al. (2019) proposed a fuzzy model-based Gaussian (F-MB-Gauss) clustering that combines a model-based Gaussian with fuzzy membership functions for clustering. In this paper, we further consider the F-MB-Gauss clustering with the leas...
Multi-omics integration-a comparison of unsupervised clustering methodologies.
Briefings in bioinformatics
Jul 19, 2019
With the recent developments in the field of multi-omics integration, the interest in factors such as data preprocessing, choice of the integration method and the number of different omics considered had increased. In this work, the impact of these f...
web-rMKL: a web server for dimensionality reduction and sample clustering of multi-view data based on unsupervised multiple kernel learning.
Nucleic acids research
Jul 2, 2019
More and more affordable high-throughput techniques for measuring molecular features of biomedical samples have led to a huge increase in availability and size of different types of multi-omic datasets, containing, for example, genetic or histone mod...
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