Prostate Tissue Core
The Michigan Center for Translational Pathology (MCTP) is associated
with the Prostate Cancer Specialized Project of Research
Excellence (SPORE) Tissue Core Lab. The SPORE Biospecimen/Pathology Core serves as a repository for invaluable prostate cancer
tissue specimens, which are utilized by the physician scientists and
researchers for unlocking the mysteries of prostate cancer development.
This repository includes tissues from radical prostectomies and tissues
from metastatic prostate cancer obtained through the rapid autopsy
The availability of this priceless
resource greatly facilitates research advances in the etiology of
prostate cancer. Critical research information from such specimens is
data linked to both clinical and pathological databases for
dissemination of comprehensive data information worldwide. Such samples
also serve as the foundation for the identification of new biomarkers,
characterization of molecular subtypes of cancer, and development of new
prognostic tests to translate research discoveries into practical
realities for patient treatment.
For more information, please visit the Michigan Prostate SPORE website.
Oncomine Research Edition is a powerful web application that integrates
and unifies high-throughput cancer profiling data so that target
expression across a large volume of cancer types can be assessed online,
in seconds. This edition is based on the original Oncomine product provided by the
University of Michigan to the academic community. It remains under a
free license for non-commercial users pursuing non-commercial purposes.
ChimeraScan is an open-source software package for the discovery of chimeric transcription between two
independent transcripts in high-throughput transcriptome sequencing
Oculus is a software package that attaches to standard aligners and
exploits read redundancy by performing streaming compression, alignment,
and decompression of input sequences. We expect that streaming read compressors such as Oculus could become a
standard addition to existing RNA-Seq and ChIP-Seq alignment pipelines,
and potentially other applications in the future as throughput