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The stereotyping of neurons in a fly brain. The red and green are neurons of two different fly brains (the same line) whose membranes were mCD8-stained by Julie Simpson. See a complete, higher-resolution movie in 3D (Unpublished data. All rights reserved.). I register the whole fly brains and map the neurons in 3D at Janelia Farm. |
Standardize 3D C. elegans image stacks by straightening the worm body. I developed worm backbone detection methods and then generated the 1-pixel spaced cutting planes to optimally reconstruct the entire worm body stack. This technique is one of the critical steps in our project in building the entire digital cell atlas for developing C. elegans. For more information, read a new Bioinformatics paper here and try a demo Matlab program for the key algorithm. BTW, don't get confused by the above animation: a C. elegans worm does not have eyes! |
Animation of computationally reconstructed 3D development time series of gene ftz (fushi tarazu) (above) and snail (below) in fly embryos, without 3D live imaging. You can find more information in this poster at 2005 Fly Meeting. (Unpublished data. All rights reserved.) |
| MSTCUT clustering of fly gene expression patterns in the eigen-embryo space. Read the ISBI2006 paper on the MinMaxPartition MSTCUT method for image clustering and the RECOMB2004 paper on hybrid Gaussian mixture model (GMM) to retrieve genes that have similar expression pattern images. |
| Minimum Redundancy Maximum Relevance (mRMR) gene selection scheme which is promising in detecting highly discriminant gene markers for cancer classification and is very efficient in optimizing the Max-Dependency/Min-Error feature selection criterion. Read a theory-paper on IEEE Transactions on Pattern Analysis and Machine Intelligence (2005), and a result-paper on Journal of Bioinformatics and Computational Biology (2005). You can run the program here. |
| Automatical detection of brain regions in 3D MR images corresponding to clinical function deficits such as mild cognitive impairment (MCI) and Alzheimer's Disease. Read the Bayesian Morphometry paper in IEEE Transactions on Medical Imaging (2004) and an application study for real MCI data. |
Selected recent publications |
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"Automatic recognition of cells (ARC) for 3D images of C. elegans" Fuhui Long, Hanchuan Peng, Xiao Liu, Stuart Kim, and Eugene Myers "Bioimage informatics: a new area of engineering biology" Hanchuan Peng "Straightening C. elegans images" Hanchuan Peng, Fuhui Long, Xiao Liu, Stuart Kim, and Eugene Myers "Data driven decomposition for multi-class classification" Jie Zhou, Hanchuan Peng, and Ching Y. Suen "Automatic image analysis for gene expression patterns of fly embryos" Hanchuan Peng, Fuhui Long, Jie Zhou, Garmay Leung, Michael Eisen, and Eugene Myers "Automatic recognition and annotation of gene expression patterns of fly embryos" Jie Zhou*, and Hanchuan Peng* (*equal contribution) "Phenotype clustering of breast epithelial cells in confocal images based on nuclear protein distribution analysis" Fuhui Long, Hanchuan Peng, Damir Sudar, Sophie Lelievre, David Knowles "Transitive closure and metric inequality of weighted graphs - detecting protein interaction modules using cliques," Chris Ding, Xiaofeng He, Hui Xiong, Hanchuan Peng, Stephen R. Holbrook "Clustering gene expression patterns of fly embryos," Hanchuan Peng, Fuhui Long, Michael Eisen, and Eugene Myers "Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy," Hanchuan Peng, Fuhui Long, and Chris Ding (Run the mRMR program.) "Minimum redundancy maximum relevance feature selection," Hanchuan Peng, Chris Ding, and Fuhui Long "Minimum redundancy feature selection from microarray gene expression data," Chris Ding, and Hanchuan Peng, (A conference version with a different set of results, but the same title, also appeared on: "Comparing in situ mRNA expression patterns of Drosophila embryos," Hanchuan Peng, and Gene Myers, "A Bayesian morphometry algorithm," Edward Herskovits, Hanchuan Peng, and Christos Davatzikos, (This is an extended journal version of the following earlier ISBI paper.) "Bayesian clustering methods for morphological analysis of MR images," Hanchuan Peng, Edward H. Herskovits, and Christos Davatzikos, An electronic demo were also given at 2002 NIH Human Brain Project Annual Meeting, A study using real BLSA Mild Cognitive Impairment data is the following report: "Bayesian analysis of morphological changes associated with mild cognitive impairment: a cross-sectional study," Hanchuan Peng, Dinggang Shen, Christos Davatzikos, Susan Resnick, and Edward H. Herskovits, "Structural search and stability enhancement of Bayesian networks," Hanchuan Peng, and Chris Ding, "Document image recognition based on template matching of component block projections," Hanchuan Peng, Fuhui Long, and Zheru Chi, |