Systems and Synthetic Biology
Systems biology is the integration of experimental and modeling approaches to dissect complex cellular phenomena. Fundamentally, systems biology aims to better quantify and comprehend the highly multivariate and interactive networks of genes, proteins, and metabolites that regulate cellular function.
The faculty in Cornell’s Meinig School apply new experimental and computational approaches to understand how these gene, signal transduction, and metabolic networks are regulated in healthy tissues and dysregulated, resulting in aberrant cell fates, in pathological settings such as development, cancer and aging. Furthermore, our researchers use modeling efforts to better engineer both novel biomolecules and new combinatorial therapeutic strategies to treat these pathophysiologies. Increasingly, our efforts aim to marry experiment and modeling at the single-cell level so as to elucidate how cell-to-cell variability arises and underlies disease progression and response to therapy. These efforts rely on connections with Cornell’s Nanobiotechnology Center, NIH-funded Physical Sciences Oncology Center, and Stem Cell Program, as well as in collaborations with clinical and research scientists at Weill Cornell Medicine.
Faculty research interests
Prof. James Antaki’s lab is involved in three application areas related to Synthetic Biology: heart-assist support systems for children and adults, development of a blood-purification system for severe malaria and multi-scale computer simulation of thrombosis in artificial circulation.
Prof. Ilana Brito’s lab pioneers systems-level methods to examine horizontal gene transfer within the human microbiome, the predominant mechanism by which pathogens acquire antibiotic resistance. The Brito Lab studies the transmission of commensal microbes between people and their environments. They employ a combination of microbial engineering, single-cell sequencing approaches, and novel computational algorithms applied to metagenomic data to better understand the relationship between human health and the microbiome.
Prof. Jonathan Butcher’s lab develops and utilizes multi-scale systems modeling to analyze molecular and cellular decisions necessary to grow and organize embryonic cardiovascular tissues. They incorporate finite-element-based growth mechanics simulation with population-based systems modeling to identify key signaling and emergent cellular decision bottlenecks that predict appropriate and malformed heart valves. These computational approaches inform bio-hybrid intervention strategies to repair congenital heart defects.
Prof. Ben Cosgrove’s lab studies how aging influences a decline in the ability of resident stem cells to regenerate adult tissues. His lab explores how alterations in intercellular communication and intracell signal transduction pathways are altered in aging. His research uses computational and experimental approaches to better understand these signaling networks at the single-cell level, and to target aberrant network functions to rejuvenate stem cells in aged tissues.
Prof. Iwijn De Vlamick leads an experimental physical genomics lab focused on the development and application of sensitive single-cell genome sequencing principles. Single-cell sequencing enables highly multivariate measurements of genomic and transcriptomic cell-to-cell variability. When combined with microscopy techniques, single cell sequencing will enable the study of the systems biology of cells in tissue microenvironments.
Prof. Mert Sabuncu’s research is focused on developing computational tools to analyze and exploit biomedical data, in particular imaging and genetic data, and primarily in the context of neurology and neuroscience. Previously at MIT and Harvard Medical School, he has recently joined Cornell to build a lab that will develop cutting-edge machine-learning algorithms for a range of biomedical applications that often involve large-scale and multi-modal datasets.
Research Area Faculty
The faculty researchers in this area exemplify the collaborative nature of the work done at Cornell Engineering.