Steven A. Garan is the Director of Bioinformatics at CREA and serves on its Advisory Board. He is also a researcher at Lawrence Berkeley National Laboratory.
While at University of California, Berkeley, he played a major role in the invention and development of the Automated Imaging Microscope System (AIMS). During his tenure there, Garan collaborated extensively with researchers from Paola S. Timiras’s laboratory on studies examining how caloric restriction maintains estrogen receptor-alpha and IGF-1 receptor immunoreactivity in specific nuclei of the mouse hypothalamus.
Garan previously served as Director of the Aging Research Centre and is widely recognized as a leading scientist in aging research. His publications span systems biology, the neuroendocrine effects of caloric restriction, and advancements in automated imaging technologies. He is best known for coining the term “Phenomics,” introduced in his abstract titled “Phenomics: a New Direction for the Study of Neuroendocrine Aging,” published in Experimental Gerontology.
Steven A. Garan was the lead scientist in developing the AIMS system alongside Warren Freitag, Jason Neudorf, and members of the UC Berkeley laboratory where the system was developed and implemented. Since the completion of its first version in 1998, multiple iterations have enhanced its performance, with the final version completed in 2007.
AIMS significantly advanced computer-assisted cell counting in neurobiology, achieving up to 97% accuracy compared to human counts for both nuclear and cytoplasmic stained tissue. The system enables highly customized regional analysis, allowing investigators to target specific anatomical regions and reduce background noise from non-immunoreactive cells. This innovation has been successfully applied to mapping the density and distribution of nuclear-expressed estrogen receptor-alpha and cytoplasmically expressed IGF-1 receptors in defined hypothalamic nuclei.
Furthermore, AIMS enables detection of intra-hypothalamic differences in receptor expression and the measurement of phenomena such as lateralization. By leveraging this technology, researchers can establish neuroendocrine biomarkers of aging and evaluate the effects of caloric restriction and gene knockout models associated with lifespan extension.
