Computational biology plays a critical role in genetics and genomic research, as a large amount of high-dimensional data generated by advanced sequencing and other molecular profiling technologies has been rapidly accumulating. With the help of cutting-edge computational tools, scientists can process and analyze large-scale multi-omics and health data to identify genetic risk factors for diseases, predict drug responses, and develop new treatments. The field of computational biology has revolutionized genetics and genomics research, making it possible to analyze and interpret vast amounts of data in ways that were not previously possible.
At the Department of Genetics and Genomic Sciences at the Icahn School of Medicine at Mount Sinai, we are passionate about harnessing the power of computational methods to delve deep into genetic and multi-omic data. Our team of experts are dedicated to unraveling the underlying causes of diseases and discovering new treatments through the analysis of large-scale data.
Some of the key research areas within computational biology in our department include developing statistical, computational, and machine/deep learning algorithms/software, analyzing large-scale multi-omic and health data, studying the genetics of complex diseases, and using computational methods to study gene/protein regulation in development and disease. Our team of researchers, data scientists, and software engineers have made significant contributions to advancing research and healthcare through the development of new methods and approaches, including:
- Algorithms to predict disease risk based on genetic and clinical/EHR information.
- Methods for SNP/SNV and gene function annotation.
- Algorithms for integrative multi-omics analysis for diagnosis, prognosis, and treatment response prediction
- Methods to predict drug response and toxicity and identify new targets for drug development based on genetic and molecular information.
- Methods to study gene and protein regulatory networks.
Our research has opened up exciting new possibilities for unlocking the potential of genetic and multi-omics data to improve human health. We are constantly striving to push the boundaries of what we know about the complex interactions between genes and disease. By developing novel computational methods and analytical tools, we are leading the way in the pursuit of new treatments and personalized medicine approaches that can make a real difference to patient outcomes.
Genetics and Genomic Sciences Faculty
- Carmen Argmann, PhD
- Samira Asgari, PhD | Lab Website
- Supinda Bunyavanich, MD | Lab Website
- Andrew Chess, MD
- Jose Clemente, PhD | Lab Website
- Gang Fang, PhD | Lab Website
- Christian Forst, PhD
- Ana Gonzalez-Reiche, PhD
- Zeynep Gumus, PhD | Lab Website
- Ke Hao, PhD
- Kuan-Lin Huang, PhD | Lab Website
- Yuval Itan, PhD | Lab Website
- Magdalena Janecka, PhD | Lab Website
- Robert Klein, PhD
- Sai Ma, PhD | Lab Website
- Edoardo Marcora, PhD
- Gaurav Pandey, PhD | Lab Website
- Lauren Peters, PhD
- Boris Reva, PhD
- Robert Sebra, PhD | Center Website
- Won-min Song, PhD | Lab Website
- Alexander Tsankov, PhD | Lab Website
- Minghui Wang, PhD
- Peter Warburton, PhD
- Guo-Cheng (GC) Yuan, PhD