Cellular Cancer Biology Research (CCBIR) Resources
The CCBIR program is developing new imaging technologies and generating data for the broader community to advance cancer research.
Cancer Complexity Knowledge Portal
Datasets, publications, and other resources generated by CCBIR, as well as other DCB research programs supported by the DCB Multi -Consortia Coordinating Center, are available in the Cancer Complexity Knowledge Portal.
CCBIR 2023 Technology Showcase Videos
Dr. Hao Zhang (Northwestern University) presents open source computational modules to enhance outreach of spectroscopic single-molecule localization microscopy (sSMLM) with the broader community.
The RainbowSTORM software for sSMLM data processing and reconstruction described in the talk is available on github.
Wei Hong Yeo (Northwestern University) shares a computational model to optimize the dual-wedge prism-based sSMLM systems for enabling high-resolution biological imaging.
Additional information about this physically informed simulation of dual-wedge prism-based sSMLM can be found in a biorxiv preprint.
Dr. Dagan Sagal (UTSW) shows a quantitative high-resolution imaging assay of single cancer cells in zebrafish models, which enables studies of cell plasticity in diverse tissue microenvironments.
Additional information about this imaging approach and how it revealed mechanistic insights into the biology of a childhood cancer can be found in a Journal of Cell Biology study.
Samir Rosas (University of Wisconsin-Madison) presents an innovative approach to mid-infrared spectrochemical tissue imaging that leverages plasmonic metasurfaces to generate surface-localized electromagnetic fields.
Additional information about this method for the imaging of tissues to capture quantitative molecular maps can be found in an Advanced Materials study.