Topology-Preserving Selection and Clustering (TPSC)

GO TO ➢ [ Summary · Vector Space Model · SOM · SVD ] ➢ [ Hybrid SOM-SVD · Two-Phase Clustering ] ➢ [ HOWTO ] ➢ [ Citations ]

Citations

We started this project (dating back from the year 2003) with the awareness: how to exploit the topological structure of multidimensional biological data might be required for in-depth mining of information relevant to a biological process of interest. Although the publication in its methodological part experiences twists and turns, its applications seem to be fruitful. If you are interested in the methodology, please cite Main Publication in Methodology. If you are also interested in the application, please further cite Main Publications in Applications. Since this project is not finished on its own, you can also give credits to Relevant Work.

Main Publication in Methodology

Fang,H, Du,Y., Xia,L., Li,J., Zhang,J., Wang,K. (2011). A topology-preserving approach for selection and clustering of multi-dimensional biological data. OMICS: A Journal of Integrative Biology 15 (7-8), 483-94 PDF

Main Publications in Applications

Fang,H., Yang,Y., Li,CL., Fu,S., Yang,Z., Jin,G., Wang,K., Zhang,J., Jin,Y. (2010). Transcriptome analysis of early organogenesis in human embryos. Developmental Cell 19 (1), 174-184 PDF

Wang,K., Fang,H., Xiao,D., Zhu,X., He,M., Pan,X., Shi,J., Zhang,H., Jia,X., Du,Y., Zhang,J. (2009). Converting redox signaling to apoptotic activities by stress-responsive regulators HSF1 and NRF2 in fenretinide treated cancer cells. PLoS ONE 4 (10), e7538 PDF

Relevant Work

Alter,O., Brown,P.O., and Botstein,D. (2000). Singular value decomposition for genome-wide expression data processing and modeling. Proc. Natl. Acad. Sci. U. S. A 97, 10101-10106.

Benjamini, Y. and Hochberg, Y. (1995). Controlling the False Discovery Rate - a Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society Series B-Methodological, 57, 289-300.

Bi,Y., Liu,R., Ye,L., Fang,H., Li,X., Wang,W., Zhang,J., Wang,K., Jiang,L., Su,T., Chen,Z., Ning,G. (2009). Gene expression profiles of thymic neuroendocrine tumors (carcinoids) with ectopic ACTH syndrome reveal novel molecular mechanism. Endocrine-Related Cancer 16 (4), 1273-82 PDF

Du,Y., Wang,K., Fang,H., Li,J., Xiao,D., Zheng,P., Chen,Y., Fan,H., Pan,X., Zhao,C., Zhang,Q., Imbeaud,S., Graudens,E., Eveno,E., Auffray,C., Chen,S., Chen,Z., Zhang,J. (2006). Coordination of intrinsic, extrinsic, and endoplasmic reticulum-mediated apoptosis by imatinib mesylate combined with arsenic trioxide in chronic myeloid leukemia. Blood 107 (4), 1582-90 PDF

Fang,H., Wang,K., and Zhang,J. (2008). Transcriptome and proteome analyses of drug interactions with natural products. Curr. Drug Metab 9, 1038-1048 PDF

Fang,H., Jin,W., Yang,Y., Jin,Y., Zhang,J., Wang,K. (2011). An organogenesis network-based comparative transcriptome analysis for understanding early human development in vivo and in vitro. BMC Systems Biology 5:108.

Holter,N.S., Mitra,M., Maritan,A., Cieplak,M., Banavar,J.R., and Fedoroff,N.V. (2000). Fundamental patterns underlying gene expression profiles: simplicity from complexity. Proc. Natl. Acad. Sci. U. S. A 97, 8409-8414.

Kohonen,T. (2001). Self-Organizing Maps. (Springer, Berlin)

Tamayo,P., Slonim,D., Mesirov,J., Zhu,Q., Kitareewan,S., Dmitrovsky,E., et al. (1999). Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. Proc. Natl. Acad. Sci. U. S. A 96, 2907-2912.

Vesanto, J. and Sulkava, M. (2002). Distance matrix based clustering of the Self-Organizing Map. Artificial Neural Networks - Icann 2002, 2415, 951-956.

Xiao,L., Wang,K., Teng,Y., and Zhang,J. (2003). Component plane presentation integrated self-organizing map for microarray data analysis. FEBS Lett. 538, 117-124.