Search results for "Cluster Analysis"

Multidimensional Clustering and Registration of Seismic Waveform Data

2011

The Three Steps of Clustering in the Post-Genomic Era: A Synopsis

2011

Clustering is one of the most well known activities in scientific investigation and the object of research in many disciplines, ranging from Statistics to Computer Science. Following Handl et al., it can be summarized as a three step process: (a) choice of a distance function; (b) choice of a clustering algorithm; (c) choice of a validation method. Although such a purist approach to clustering is hardly seen in many areas of science, genomic data require that level of attention, if inferences made from cluster analysis have to be of some relevance to biomedical research. Unfortunately, the high dimensionality of the data and their noisy nature makes cluster analysis of genomic data particul…

Computational cluster validation for microarray data analysis: experimental assessment of Clest, Consensus Clustering, Figure of Merit, Gap Statistic…

2008

Abstract Background Inferring cluster structure in microarray datasets is a fundamental task for the so-called -omic sciences. It is also a fundamental question in Statistics, Data Analysis and Classification, in particular with regard to the prediction of the number of clusters in a dataset, usually established via internal validation measures. Despite the wealth of internal measures available in the literature, new ones have been recently proposed, some of them specifically for microarray data. Results We consider five such measures: Clest, Consensus (Consensus Clustering), FOM (Figure of Merit), Gap (Gap Statistics) and ME (Model Explorer), in addition to the classic WCSS (Within Cluster…

Business models in Spanish industry : a taxonomy-based efficacy analysis

2010

The present study provides a conceptualization of the business model construct from which a multi-dimensional evaluation tool is developed that provides the basis for drawing up a taxonomy and analysing its comparative efficacy. The empirical data was obtained from a sampling of 159 Spanish business organisations. The cluster analysis revealed the existence of four business models that were designated as “multidivisional”, “integrated”, “hybrid” and “network”. The results also indicate that the adoption of a certain business model is not enough to attain superior performance, highlighting the need to consider other contingent factors.

Data-Driven Interactive Multiobjective Optimization Using a Cluster-Based Surrogate in a Discrete Decision Space

2019

In this paper, a clustering based surrogate is proposed to be used in offline data-driven multiobjective optimization to reduce the size of the optimization problem in the decision space. The surrogate is combined with an interactive multiobjective optimization approach and it is applied to forest management planning with promising results. peerReviewed

Beyond Tandem Analysis: Joint Dimension Reduction and Clustering in R

2019

We present the R package clustrd which implements a class of methods that combine dimension reduction and clustering of continuous or categorical data. In particular, for continuous data, the package contains implementations of factorial K-means and reduced K-means; both methods combine principal component analysis with K-means clustering. For categorical data, the package provides MCA K-means, i-FCB and cluster correspondence analysis, which combine multiple correspondence analysis with K-means. Two examples on real data sets are provided to illustrate the usage of the main functions.

Discrete cortical representations and their stability in the presence of synaptic turnover

2015

Population imaging in mouse auditory cortex revealed clustering of neural responses to brief complex sounds: the activity of a local population typically falls close to one out of a small number of observed states [1]. These clusters appear to group sets of auditory stimuli into a discrete set of activity patterns and could thereby form the basis for representations of sound categories. However, to be useful for the brain, such representations should be robust against fluctuations in the underlying circuitry, which are significant even in the absences of any explicit learning paradigm [2]. Here we introduce a novel firing rate based circuit model of mouse auditory cortex to study the emerge…

Comparative parallel characterization of particle populations with two mass spectrometric systems LAMPAS 2 and SPASS

2006

Abstract Two transportable laser mass spectrometers, Single Particle Analysis and Sizing System (SPASS) and Laser Mass Analyzer for Particles in the Airborne State (LAMPAS 2), have been applied to investigate the dependence of spectra patterns on instrumental parameters and data evaluation procedures in an inter-comparison experiment. Laboratory experiments showed the spectral response of both instruments for mineral particles before and after heterogeneous reactions. During a period of 47 h, both instruments determined size and chemical composition of several thousand single particles of an ambient particle population. Time-resolved evaluation (1-h resolution) of specific ion signals, whic…

Population differentiation of the European pond turtle (Emys orbicularis) in Poland inferred by the analysis of mitochondrial and microsatellite DNA …

2013

We investigated the genetic diversity of Polish populations of the European pond turtle (Emys orbicularis) using complete sequences of the mitochondrial cytochrome b gene and allelic variation at thirteen microsatellite loci. We collected data from 146 turtles from 28 locations covering most of the species’ range in Poland. Our results showed a low haplotype diversity and high levels of microsatellite diversity in all populations. We applied two Bayesian approaches using the multilocus data and determined relationships of mtDNA haplotypes by constructing a parsimony network. We observed relatively consistent results of the two Bayesian clustering methods and largely concordant differentiati…

Sperm kinematics and morphometric subpopulations analysis with CASA systems: a review

2019

Sperm kinematics and morphometric subpopulations analysis with CASA systems: a review. The subjective evaluation of seminal quality has given way to the use of objective assessment techniques by CASA technology (computer-assisted semen analysis). The application of principal components (PC) and clustering methods to reveal subpopulations of spermatozoa is a powerful tool to evaluate raw semen and processed cell suspensions, but not many researchers are aware of the technique. PC analysis is a multivariate statistical method that reduces the number of variables used in subsequent calculations used to describe the data. By integrating the original variables according to their coherence in a d…