Journal ArticleDOI
Noise-robust soft clustering of gene expression time-course data
TLDR
To overcome the limitations of hard clustering, this work applied soft clustering which offers several advantages for researchers, including more noise robust and a priori pre-filtering of genes can be avoided.Abstract:
Clustering is an important tool in microarray data analysis. This unsupervised learning technique is commonly used to reveal structures hidden in large gene expression data sets. The vast majority of clustering algorithms applied so far produce hard partitions of the data, i.e. each gene is assigned exactly to one cluster. Hard clustering is favourable if clusters are well separated. However, this is generally not the case for microarray time-course data, where gene clusters frequently overlap. Additionally, hard clustering algorithms are often highly sensitive to noise. To overcome the limitations of hard clustering, we applied soft clustering which offers several advantages for researchers. First, it generates accessible internal cluster structures, i.e. it indicates how well corresponding clusters represent genes. This can be used for the more targeted search for regulatory elements. Second, the overall relation between clusters, and thus a global clustering structure, can be defined. Additionally, soft clustering is more noise robust and a priori pre-filtering of genes can be avoided. This prevents the exclusion of biologically relevant genes from the data analysis. Soft clustering was implemented here using the fuzzy c-means algorithm. Procedures to find optimal clustering parameters were developed. A software package for soft clustering has been developed based on the open-source statistical language R. The package called Mfuzz is freely available.read more
Citations
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Journal ArticleDOI
Quantitative Time-Resolved Phosphoproteomic Analysis of Mast Cell Signaling
Lulu Cao,Kebing Yu,Cindy Banh,Vinh Nguyen,Anna Ritz,Benjamin J. Raphael,Yuko Kawakami,Toshiaki Kawakami,Arthur R. Salomon +8 more
TL;DR: A far more extensive array of tyrosine phosphorylation events than previously known is revealed, including novelosphorylation sites on canonical mast cell signaling molecules, as well as unexpected pathway components downstream of FcεRI activation.
Journal ArticleDOI
A differentiation-based microRNA signature identifies leiomyosarcoma as a mesenchymal stem cell-related malignancy
Laura S. Danielson,Silvia Menendez,Camille Stephan-Otto Attolini,Maria V. Guijarro,Maria Bisogna,Jian-Jun Wei,Nicholas D. Socci,Douglas A. Levine,Franziska Michor,Eva Hernando +9 more
TL;DR: It is demonstrated that miRNAs are required for full smooth muscle cell (SMC) differentiation of bone marrow-derived human mesenchymal stem cells (hMSCs) and shown that this signature, along with miRNA profiles for ULMS and ULM, are able to subclassify tumors of smooth muscle origin along SM differentiation.
Journal ArticleDOI
Molecular Insights into Reprogramming-Initiation Events Mediated by the OSKM Gene Regulatory Network
Nancy Mah,Ying Wang,Mei-Chih Liao,Alessandro Prigione,Justyna Jozefczuk,Björn Lichtner,Katharina Wolfrum,Manuela Haltmeier,Max Flöttmann,Martin Schaefer,Alexander Hahn,Ralf Mrowka,Edda Klipp,Miguel A. Andrade-Navarro,James Adjaye +14 more
TL;DR: Overall, the results suggest three strategies to improve reprogramming efficiency employing: 1) anti-inflammatory modulation of innate immune response, 2) pre-selection of cells expressing pluripotency-associated surface antigens, 3) activation of specific interaction paths that amplify the pluripOTency signal.
BookDOI
Functional genomics and evolution of photosynthetic systems
Robert L. Burnap,Willem Vermaas +1 more
TL;DR: Functional Genomics in an Ecological and Evolutionary Context: Maximizing the Value of Genomes in Systems Biology, which also discusses the Physiology and Functional Genomics of Cyanobacterial Hydrogenases and Approaches toward Biohydrogen Production.
Journal ArticleDOI
Iron Deprivation in Synechocystis: Inference of Pathways, Non-coding RNAs, and Regulatory Elements from Comprehensive Expression Profiling
Miguel A. Hernández-Prieto,Verena Schön,Jens Georg,Luísa Barreira,João Varela,Wolfgang R. Hess,Matthias E. Futschik +6 more
TL;DR: The genome-wide expression profiling indicates an unprecedented complexity in the iron regulatory network of cyanobacteria.
References
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Journal ArticleDOI
Cluster analysis and display of genome-wide expression patterns
TL;DR: A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression, finding in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function.
Book
Pattern Recognition with Fuzzy Objective Function Algorithms
TL;DR: Books, as a source that may involve the facts, opinion, literature, religion, and many others are the great friends to join with, becomes what you need to get.
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