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Techniques for clustering gene expression data [PDF]
, 2008 Many clustering techniques have been proposed for the analysis of gene expression data obtained from microarray experiments. However, choice of suitable method(s) for a given experimental dataset is not straightforward. Common approaches do not translate
Kerr, Gráinne +7 more
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Anytime Hierarchical Clustering
CoRR, 2014 We propose a new anytime hierarchical clustering method that iteratively transforms an arbitrary initial hierarchy on the configuration of measurements along a sequence of trees we prove for a fixed data set must terminate in a chain of nested partitions that satisfies a natural homogeneity requirement.
Ömür Arslan, Daniel E. Koditschek
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SMART: Unique splitting-while-merging framework for gene clustering [PDF]
, 2014 Copyright @ 2014 Fa et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are ...
Fa, R +8 more
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genieclust: Fast and robust hierarchical clustering
SoftwareX, 2021 genieclust is an open source Python and R package that implements the hierarchical clustering algorithm called Genie. This method frequently outperforms other state-of-the-art approaches in terms of clustering quality and speed, supports various ...
Marek Gagolewski
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Scalable adaptive hierarchical clustering [PDF]
IEEE Communications Letters, 2002 We propose a new application-level clustering algorithm capable of building an overlay spanning tree among participants of large multicast sessions, without any specific help from the network routers. This algorithm is based on a unique definition of zones around nodes and an innovative adaptive cluster size distribution.
MATHY L. +3 more
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BarekengCluster analysis is a method of grouping data into certain groups based on similar characteristics. This research aims to group districts/cities in East Java Province in 2021 based on HIV cases using hierarchical cluster analysis (AGNES), non ...
Dwi Ayu Lusia +3 more
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ESPRIT-Forest: Parallel clustering of massive amplicon sequence data in subquadratic time. [PDF]
PLoS Computational Biology, 2017 The rapid development of sequencing technology has led to an explosive accumulation of genomic sequence data. Clustering is often the first step to perform in sequence analysis, and hierarchical clustering is one of the most commonly used approaches for ...
Yunpeng Cai +6 more
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Coping With New Challengens for Density-Based Clustering [PDF]
, 2004 Knowledge Discovery in Databases (KDD) is the non-trivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data.
Kröger, Peer
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Covariance matrix filtering with bootstrapped hierarchies.
PLoS ONE, 2021 Cleaning covariance matrices is a highly non-trivial problem, yet of central importance in the statistical inference of dependence between objects. We propose here a probabilistic hierarchical clustering method, named Bootstrapped Average Hierarchical ...
Christian Bongiorno, Damien Challet
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A Data-Driven Clustering Recommendation Method for Single-Cell RNA-Sequencing Data
Tsinghua Science and Technology, 2021 Recently, the emergence of single-cell RNA-sequencing (scRNA-seq) technology makes it possible to solve biological problems at the single-cell resolution.
Yu Tian +5 more
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