1Watson School of Biological Sciences, 2Cold Spring Harbor Laboratory, 3Departments of Medical Genetics, University of Oslo and Oslo University Hospital
We describe a method for imaging response to anti-cancer treatment in vivo and at single cell resolution.
Published March 24, 2013. Keywords: Cancer Biology, Medicine, Molecular Biology, Cellular Biology, Biomedical Engineering, Genetics, Oncology, Pharmacology, Surgery, Tumor Microenvironment, Intravital imaging, chemotherapy, Breast cancer, time-lapse, mouse models, cancer cell death, stromal cell migration, cancer, imaging, transgenic, animal model
1Department of Applied Mathematics & Statistics, Stony Brook University, 2Computational Biology and Bioinformatics, Cold Spring Harbor Laboratory, 3Department of Molecular and Cell Biology, University of Texas at Dallas
Our Bayesian Change Point (BCP) algorithm builds on state-of-the-art advances in modeling change-points via Hidden Markov Models and applies them to chromatin immunoprecipitation sequencing (ChIPseq) data analysis. BCP performs well in both broad and punctate data types, but excels in accurately identifying robust, reproducible islands of diffuse histone enrichment.
Published December 10, 2012. Keywords: Genetics, Bioinformatics, Genomics, Molecular Biology, Cellular Biology, Immunology, Chromatin immunoprecipitation, ChIP-Seq, histone modifications, segmentation, Bayesian, Hidden Markov Models, epigenetics
1Cold Spring Harbor Laboratory
The in situ hybridization protocol described here allows a direct localization of mRNA and small RNA expression at the cellular level with high sensitivity and specificity. The procedure is optimized for paraffin-embedded plant tissue sections, is applicable to a wide range of plants and tissues, and can be completed within ten days.
Published November 23, 2011. Keywords: Plant Biology, In Situ hybridization, RNA localization, expression analysis, plant, DIG-labeled probe