| Ihor Lemischka [web]
|
Professor of Molecular Biology
University of Princeton, USA
The laboratory of Dr. Ihor Lemischka brings molecular expertise,
and a long history of in vivo, in vitro, and genomic analyses of
murine hematopoietic stem and progenitor cells. The laboratory also
maintains the Stem Cell Database (SCDb).
|
|
| Kateri Moore [web]
|
Research Molecular Biologist
University of Princeton, USA
The laboratory of Dr. Kateri Moore is focused on the hematopoietic
microenvironment and has developed in in vitro system that is very
potent in its abilities to support the long-term functional activities
of both mouse and human stem and progenitor cells. The laboratory also
maintains the Stromal Cell Database (StroCDB).
|
|
| Paul Simmons [web]
|
Associate Professor
Peter MacCallum Cancer Institute, Melbourne, Australia
The laboratory of Dr. Paul Simmons provides expertise in the
purification of the human hematopoietic hierarchy obtained from
distinct tissue sources. This laboratory also provides a broad range
of quantitative in intro and murine xenograft in vivo assays to
accurately assess the biological activities of cell populations to be
used in molecular analyses.
|
|
| Esmail Zanjani [web]
|
Professor, Dept. of Animal Biotechnology
University of Nevada, USA
The laboratory of Dr. Esmail Zanjani brings expertise in the in utero sheep xenograft system as an assay for human hematopoietic stem cell activity.
|
|
| Chris Stoeckert [web]
|
Research Associate Professor, Dept. of Genetics
University of Pennsylvania, USA
The laboratory of Dr. Chris Stoeckert brings state-of-the-art
computational and bioinformatic expertise. Of primary importance are
the Genomics Unified Schema (GUS)
and the RNA Abundance Database (RAD). |
|
| Lyle Ungar [web]
|
Associate Professor of Computer and Information Science
University of Pennsylvania, USA
The group of Dr. Lyle Ungar will focus on the higher level
computational analyses of gene expression data from stem and
progenitor cells. In particular, the efforts will be made to identify
regulatory networks from large amounts of DNA microarray gene
expression data.
|