Abstract:
The realms of genome research and medicine have been prolific in generating vast amounts of data. Yet, the surge in data has not proportionately translated into a deeper exploration of the biology associated with genes that have a low-profile in the biomedical literature, especially those not frequently mentioned prior to the completion of the Human Genome Project in 2003.

Addressing this discrepancy, I have employed a combination of multi-omic analyses and scientometric methods to pinpoint and understand the obstacles that hinder further research into these genes. This approach, which minimizes the need for extensive biological experimentation, has already yielded promising opportunities. A notable accomplishment is my identification of a primary cause of gene expression changes in aging across humans and animals, termed Gene Length-dependent Transcription Decline. In addition to this, in unpublished work, I am collaborating with a major funding agency. Together, we're using Artificial Intelligence and historical archives to understand the optimal ways to foster and sustain innovation in the fields of genome research and medicine.

My aim is to expand on this groundwork to develop a robust and influential research program that actively pursues the under-investigated realms of biology, particularly in the context of aging. This approach has immense potential to pave the way for my trainees to emerge as pioneers in future research fields. According to scientometric data, Saudi Arabia is a hub for research into under-investigated genes, aligning with the nation's Vision 2030 and highlighting the significance of genetic variants of these genes for patients and their families. This congruence underscores the relevance and impact of my research direction, both regionally and globally.

Bio:
Thomas Stoeger studied molecular biology in the University of Vienna in the laboratory of Juergen Knoblich, where he contributed to genome-wide screens in the fruit fly Drosophila melanogaster. For his PhD he joined the laboratory of Lucas Pelkmans at the University of Zurich, where he co-developed experimental and computational approaches for the initial generation of image-based spatial transcriptomics. For this work he received the Annual Award of the University of Zurich for the best PhD thesis in the sciences. To combine discovery based biology with quantitative studies of science, he subsequently did his Postdoc at Northwestern University, Chicago. There he was an awarded a highly competitive and interdisciplinary data science scholarship, and was mentored by Luis Amaral, Scott Budinger, Richard Morimoto and Elizabeth McNally. Supported with an R00 grant of the National Institute of Aging, he joined Northwestern University as Assistant Professor in October 2023.