@article {79,
	title = {BioSig3D: High Content Screening of Three-Dimensional Cell Culture Models},
	journal = {PLoS One},
	volume = {11},
	year = {2016},
	month = {2016},
	pages = {e0148379},
	abstract = {<p>BioSig3D is a computational platform for high-content screening of three-dimensional (3D) cell culture models that are imaged in full 3D volume. It provides an end-to-end solution for designing high content screening assays, based on colony organization that is derived from segmentation of nuclei in each colony. BioSig3D also enables visualization of raw and processed 3D volumetric data for quality control, and integrates advanced bioinformatics analysis. The system consists of multiple computational and annotation modules that are coupled together with a strong use of controlled vocabularies to reduce ambiguities between different users. It is a web-based system that allows users to: design an experiment by defining experimental variables, upload a large set of volumetric images into the system, analyze and visualize the dataset, and either display computed indices as a heatmap, or phenotypic subtypes for heterogeneity analysis, or download computed indices for statistical analysis or integrative biology. BioSig3D has been used to profile baseline colony formations with two experiments: (i) morphogenesis of a panel of human mammary epithelial cell lines (HMEC), and (ii) heterogeneity in colony formation using an immortalized non-transformed cell line. These experiments reveal intrinsic growth properties of well-characterized cell lines that are routinely used for biological studies. BioSig3D is being released with seed datasets and video-based documentation.</p>},
	issn = {1932-6203},
	doi = {10.1371/journal.pone.0148379},
	author = {Bilgin, Cemal Cagatay and Fontenay, Gerald and Cheng, Qingsu and Hang Chang and Ju Han and Parvin, Bahram}
}
@article {81,
	title = {Breast fibroblasts modulate early dissemination, tumorigenesis, and metastasis through alteration of extracellular matrix characteristics},
	journal = {Neoplasia},
	volume = {15},
	year = {2013},
	month = {2013 Mar},
	pages = {249-62},
	abstract = {<p>A wealth of evidence has now demonstrated that the microenvironment in which a tumorigenic cell evolves is as critical to its evolution as the genetic mutations it accrues. However, there is still relatively little known about how signals from the microenvironment contribute to the early events in the progression to malignancy. To address this question, we used a premalignant mammary model to examine how fibroblasts, and the extracellular matrix (ECM) proteins they secrete, influence progression to malignancy. Their effect on metastatic malignant cells was also assessed for comparison. We found that carcinoma-associated fibroblasts, and the distinct aligned ECM they deposit, can cause both premalignant and malignant mammary epithelial cells to assume a mesenchymal morphology that is associated with increased dissemination and metastasis, while benign reduction mammoplasty fibroblasts favor the maintenance of an epithelial morphology and constrain early dissemination, tumor growth, and metastasis. Our results suggest that normalizing the organization of the ECM could be effective in limiting systemic dissemination and tumor growth.</p>},
	keywords = {Animals, Breast, Cell Line, Cell Transformation, Coculture Techniques, Epithelial Cells, Experimental, Extracellular Matrix, Extracellular Signal-Regulated MAP Kinases, Female, Fibroblasts, Humans, Lung Neoplasms, Mammary Neoplasms, Neoplasm Metastasis, Neoplastic, Phenotype, Proto-Oncogene Proteins c-jun, rho GTP-Binding Proteins, Signal Transduction, Transforming Growth Factor beta, Tumor},
	issn = {1476-5586},
	author = {Dumont, Nancy and Liu, Bob and DeFilippis, Rosa Anna and Hang Chang and Rabban, Joseph T and Karnezis, Anthony N and Tjoe, Judy A and Marx, James and Parvin, Bahram and Tlsty, Thea D}
}
@conference {32,
	title = {Batch-invariant nuclear segmentation in whole mount histology sections},
	booktitle = {9th {IEEE} International Symposium on Biomedical Imaging: From Nano to Macro, {ISBI} 2012, May 2-5, 2012, Barcelona, Spain, Proceedings},
	year = {2012},
	doi = {10.1109/ISBI.2012.6235683},
	url = {http://dx.doi.org/10.1109/ISBI.2012.6235683},
	author = {Hang Chang and Leandro A. Loss and Paul T. Spellman and Alexander Borowsky and Bahram Parvin}
}
@conference {45,
	title = {A Bayesian approach for image segmentation with shape priors},
	booktitle = {2008 {IEEE} Computer Society Conference on Computer Vision and Pattern Recognition {(CVPR} 2008), 24-26 June 2008, Anchorage, Alaska, {USA}},
	year = {2008},
	doi = {10.1109/CVPR.2008.4587430},
	url = {http://dx.doi.org/10.1109/CVPR.2008.4587430},
	author = {Hang Chang and Qing Yang and Bahram Parvin}
}
