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Mount Sinai, RPI to Collaborate on Bioinformatics Apps as Part of Academic Research Pact

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This week, the Icahn School of Medicine at Mount Sinai and Rensselaer Polytechnic Institute announced an agreement to collaborate on educational programs, research, and development of new diagnostic tools and treatments that promote human health.

According to the partners, the collaboration will include the development of computational tools that are capable of analyzing genomic data and generating predictive models of diseases.

In an email to BioInform, Andrew Kasarskis, vice chairman and associate professor in Mount Sinai’s genetics and genomic sciences department and co-director of the Icahn Institute for Genomics and Multiscale Biology, said that researchers at his institution are pursuing “a wide variety of problems in genomics and multiscale biology … many of which have potential for collaboration with RPI.”

Collaborative projects could focus on things like “automated and correct genome assembly,” he said. Currently, researchers at Mount Sinai are working to “leverage the power of long- and short-read sequencing technologies … to facilitate this in both microbes and more complex eukaryotes,” he said.

A second set of projects would focus on the development of tools for genome comparison, appropriate reference genome selection, and genome interpretation.

“This work is important to our understanding of fundamental human biology, but it also provides … data for modeling evolution and underpins and interpretation of clinical genome sequencing of somatic and cancer genomes,” Kasarskis said.

Other projects would focus on building predictive models of biological systems that include molecular profiling and clinical data, as well as exploring the utility of these models across populations.

On that front, “we are extending the inference models we have … built from genetic, gene expression, and clinical data in human and model organism populations to include measures of the microbiome and models that regularly consider interaction between tissues in the host and between the host and its microbiome,” he explained.

In addition, “we are working to combine these top-down inference models with bottom-up mechanistic models in new network structure learning algorithms,” he said.

Finally, “the number of molecules we assay in RNA-seq and other molecular profiling techniques has exploded the number of nodes one may consider in a network model, and that calls for new, more efficient algorithms to tackle these problems,” he said.

Other aspects of the Mount Sinai-RPI collaboration include plans to develop complementary research programs in neuroscience and neurological diseases, genomics, imaging, orthopedics, cancer, cardiovascular disease, and scientific and clinical targets.

Mount Sinai and RPI will also seek joint funding for research programs in precision medicine, drug discovery, stem cell biology, robotics and robotic surgery, novel imaging techniques, cellular engineering, and computational neurobiology.

Furthermore, the institutions will work together to develop and use novel neuroimaging techniques and neurotechnologies to better understand and treat neurological disorders.

Other plans include developing joint graduate educational programs in multiple areas of translational basic science. The partnership will offer new scholarly research opportunities for Mount Sinai medical students, and new research and clinical opportunities for RPI students, as well as cross-listed courses for students of both institutions, along with new summer programs for undergraduates, graduate students, and postdoctoral researchers.

“It is important to realize that this partnership with RPI goes way beyond research,” Kasarskis said. “There is a huge need for quantitatively trained biologists and clinicians, as well as engineers familiar with biomedical engineering problems, and this partnership with RPI will expose trainees at all levels to the best problems modern medicine has to offer … That is where I see the real long-term value of this partnership.”

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