Many fields,such as neuroscience,are experiencing the vast prolife ration of cellular data,underscoring the need fo r organizing and interpreting large datasets.A popular approach partitions data into manageable subse...
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Many fields,such as neuroscience,are experiencing the vast prolife ration of cellular data,underscoring the need fo r organizing and interpreting large datasets.A popular approach partitions data into manageable subsets via hierarchical clustering,but objective methods to determine the appropriate classification granularity are *** recently introduced a technique to systematically identify when to stop subdividing clusters based on the fundamental principle that cells must differ more between than within *** we present the corresponding protocol to classify cellular datasets by combining datadriven unsupervised hierarchical clustering with statistical *** general-purpose functions are applicable to any cellular dataset that can be organized as two-dimensional matrices of numerical values,including molecula r,physiological,and anatomical *** demonstrate the protocol using cellular data from the Janelia MouseLight project to chara cterize morphological aspects of neurons.
Extracting biological significance from a large microarray dataset using data mining clustering technique is an important process in bioinformatics. In this paper, a microarray dataset (matrix 504 x 227) made availabl...
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ISBN:
(纸本)1402052626
Extracting biological significance from a large microarray dataset using data mining clustering technique is an important process in bioinformatics. In this paper, a microarray dataset (matrix 504 x 227) made available by SAMSI institute, was used as the base sample to develop a new demo web-based clustering system that exploits the improved efficiency and functionality of PHP/MYSQL technology. The clustering algorithms and robustness of PHP/MYSQL produced categorized microarray data that can be associated with diseases with improved visualizations.
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