A comprehensive survey of clustering algorithms
Data analysis is used as a common method in modern science research, which is across
communication science, computer science and biology science. Clustering, as the basic …
communication science, computer science and biology science. Clustering, as the basic …
Machine learning and statistical methods for clustering single-cell RNA-sequencing data
Single-cell RNAsequencing (scRNA-seq) technologies have enabled the large-scale whole-
transcriptome profiling of each individual single cell in a cell population. A core analysis of …
transcriptome profiling of each individual single cell in a cell population. A core analysis of …
Long-read sequencing of 3,622 Icelanders provides insight into the role of structural variants in human diseases and other traits
Long-read sequencing (LRS) promises to improve the characterization of structural variants
(SVs). We generated LRS data from 3,622 Icelanders and identified a median of 22,636 SVs …
(SVs). We generated LRS data from 3,622 Icelanders and identified a median of 22,636 SVs …
A survey on filter techniques for feature selection in gene expression microarray analysis
A plenitude of feature selection (FS) methods is available in the literature, most of them
rising as a need to analyze data of very high dimension, usually hundreds or thousands of …
rising as a need to analyze data of very high dimension, usually hundreds or thousands of …
Survey of clustering algorithms
Data analysis plays an indispensable role for understanding various phenomena. Cluster
analysis, primitive exploration with little or no prior knowledge, consists of research …
analysis, primitive exploration with little or no prior knowledge, consists of research …
Model-based clustering, discriminant analysis, and density estimation
C Fraley, AE Raftery - Journal of the American statistical …, 2002 - Taylor & Francis
Cluster analysis is the automated search for groups of related observations in a dataset.
Most clustering done in practice is based largely on heuristic but intuitively reasonable …
Most clustering done in practice is based largely on heuristic but intuitively reasonable …
Advances in meta-heuristic optimization algorithms in big data text clustering
This paper presents a comprehensive survey of the meta-heuristic optimization algorithms
on the text clustering applications and highlights its main procedures. These Artificial …
on the text clustering applications and highlights its main procedures. These Artificial …
A survey of clustering data mining techniques
P Berkhin - Grou** multidimensional data: Recent advances in …, 2006 - Springer
Clustering is the division of data into groups of similar objects. In clustering, some details are
disregarded in exchange for data simplification. Clustering can be viewed as a data …
disregarded in exchange for data simplification. Clustering can be viewed as a data …
TM4: a free, open-source system for microarray data management and analysis
AI Saeed, V Sharov, J White, J Li, W Liang… - …, 2003 - Taylor & Francis
BioTechniques 34: 374-378 (February 2003) supported, MADAM is being adapted to read
and write MAGE-ML, the XML data exchange format being developed by an international …
and write MAGE-ML, the XML data exchange format being developed by an international …
Using Bayesian networks to analyze expression data
DNA hybridization arrays simultaneously measure the expression level for thousands of
genes. These measurements provide a “snapshot” of transcription levels within the cell. A …
genes. These measurements provide a “snapshot” of transcription levels within the cell. A …