ArticleBioinformatics (Oxford, England)2011
SC²ATmd: a tool for integration of the figure of merit with cluster analysis for gene expression data.
Article in Bioinformatics (Oxford, England), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Article
- A brief procedure for big data analysis of gene expression.Animal models and experimental medicine · 2018Review
- Identification of Transcriptional and Receptor Networks That Control Root Responses to Ethylene.Plant physiology · 2018Article
- Local Auxin Biosynthesis Mediated by a YUCCA Flavin Monooxygenase Regulates Haustorium Development in the Parasitic Plant Phtheirospermum japonicum.The Plant cell · 2016Article
- Impact of the Type I Interferon Receptor on the Global Gene Expression Program During the Course of Dendritic Cell Maturation Induced by Polyinosinic Polycytidylic Acid.Journal of interferon & cytokine research : the official journal of the International Society for Interferon and Cytokine Research · 2016Article
- Article
- A kinetic analysis of the auxin transcriptome reveals cell wall remodeling proteins that modulate lateral root development in Arabidopsis.The Plant cell · 2013Article
- Disease progression and phasic changes in gene expression in a mouse model of osteoarthritis.PloS one · 2013Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
unlabelledStandard and Consensus Clustering Analysis Tool for Microarray Data (SC²ATmd) is a MATLAB-implemented application specifically designed for the exploration of microarray gene expression data via clustering. Implementation of two versions of the clustering validation method figure of merit allows for performance comparisons between different clustering algorithms, and tailors the cluster analysis process to the varying characteristics of each dataset. Along with standard clustering algorithms this application also offers a consensus clustering method that can generate reproducible clusters across replicate experiments or different clustering algorithms. This application was designed specifically for the analysis of gene expression data, but may be used with any numerical data as long as it is in the right format. AVAILABILITY: SC²ATmd may be freely downloaded from http://www.compbiosci.wfu.edu/tools.htm.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.