Human health has been transformed by our collective capacity to engineer immunity — from the pivotal development of the smallpox vaccine to the curative potential of recent cancer immunotherapies. These examples motivate our research program that is conducted at the interface of Engineering and Immunology, and where we develop biomedical technologies and applications that shape a diverse array of immunological systems.
The questions that are central to our exploration include: How do we begin to study an individual's repertoire of well over one billion immune cells when current technologies only allow us to study a handful of cells at a time? What are the biomarkers of immunological health as the body responds to disease and ageing, and how may these indicators trigger clinical decisions? And how can we genetically rewire immune cells to provide them with entirely new functions to better fight complex diseases such as cancer?
To aid in our studies, we use high-throughput technologies such as next-generation sequencing and quantitative mass spectrometry, and pioneer the development of micro- and nanotechnologies in order to achieve our goals. We focus on clinical problems in cancer, infectious diseases and autoimmunity, and ultimately strive to translate key findings into therapies for patients.
The Heart Regeneration Lab focuses on using genes and chemicals to pace and regenerate the heart. We are based at Emory University in Pediatrics and BME in the Wallace H. Coulter Department of Biomedical Engineering of Georgia Tech and Emory University.
Diagnostic imaging and patient-specific image-guided therapeutics including cancer imaging and diagnosis.
Emelianov’s research interests are in the areas of intelligent diagnostic imaging and patient-specific image-guided therapeutics including cancer imaging and diagnosis, the detection and treatment of atherosclerosis, the development of imaging and therapeutic nanoagents, guided drug delivery and controlled release, simultaneous anatomical, functional, cellular and molecular imaging, multi-modal imaging, and image-guided therapy.
James Dahlman is an Assistant Professor in the Georgia Tech BME Department. He studied RNA design and gene editing as a post-doc with Feng Zhang at the Broad Institute, and received his PhD from MIT and Harvard Medical School in 2014, where he studied RNA delivery with Robert Langer and Daniel Anderson.
The Lab for Precision Therapies at Georgia Tech, also called the 'Dahlman Lab', works at the interface of drug delivery, nanotechnology, genomics, and gene editing. James has designed nanoparticles that deliver RNAs to the lung and heart; these nanoparticles have been used by over ten labs across the US to date. He has also developed targeted in vivo combination therapies; nanoparticles deliver multiple therapeutic RNAs at once, in order to manipulate several nodes on a single disease pathway. More recently, he developed a method to quantify the targeting, biodistribution, and pharmacokinetics of dozens to hundreds of distinct nanoparticles at once directly in vivo.
Finally, James uses molecular biology to rationally design the genetic drugs he delivers. He recently reported 'dead' guide RNAs; these engineered RNAs can be used to simultaneously up- and down-regulate different genes in a single cell using Cas9.
James has won the NSF, NDSEG, NIH OxCam, Whitaker Graduate, and LSRF Fellowships, the Weintraub Graduate Thesis Award, and was recently named a Bayer Young Investigator and Parkinson's Disease Foundation Young Investigator. He has had significant help along the way. Besides having great scientific advisors, James has been lucky to mentor excellent students, including two that were finalists for the Rhodes Scholarship.
In the Dahlman Lab, we focus on the interface between nanotechology, molecular biology, and genomics. We design drug delivery vehicles that target RNA and other nucleic acids to cells in the body. We have delivered RNAs to endothelial cells, and have treated heart disease, cancer, inflammation, pulmonary hypertension, emphysema, and even vein graft disease. Because we can deliver RNAs to blood vessels at low doses, sometimes we decide to deliver multiple therapeutic RNAs to the same cell at once. These 'multigene therapies' have been used to treat heart disease and cancer. Why is this important? Most diseases are caused by combinations of genes, not a single gene. We also rationally design the nucleic acids we want to deliver. For example, we re-engineered the Cas9 sgRNA to turn on genes, instead of turning them off. This enabled us to easily turn on gene A and turn off gene B in the same cell.
Cell biomechanics, systems biology, multiscale modeling and simulations, vasculogenesis, metastasis
His current research is focused on developing and applying computational methods, including mathematical modeling, simulations, and computer vision approaches to understand complex multi-scale physiological processes including vasculogenesis, morphogenesis, wound healing, and cancer.
We focus on developing and applying label-free linear and nonlinear optical methods, along with advanced signal processing methods, to gain access to novel forms of functional and molecular contrast for a variety of biomedical applications.
Peng Qiu received his B.S. degree from the University of Science and Technology of China, and a Ph.D. degree from the University of Maryland College Park, both in electrical engineering. After spending three years as a postdoctoral fellow in the Center for Cancer Systems Biology at Stanford, and three years as an assistant professor in the Department of Bioinformatics and Computational Biology at UT MD Anderson Cancer Center, he joined the Department of Biomedical Engineering at the Georgia Institute of Technology and Emory University.
Bioinformatics and computational biology, machine learning, data integration, progression analysis, single-cell analysis, flow cytometry
Bioinformatics and computational biology, machine learning, data integration, progression analysis, single-cell analysis, and flow cytometry.
My main research interests are in bioinformatics and computational biology, focusing on statistical signal processing, machine learning, control systems and optimization. The following are some specific topics that I've been working on:
Extracting the cellular hierarchy underlying high-dimensional single-cell data
Discovering Biological Progression underlying Gene Expression Data
Simultaneous classification and class discovery
Information theoretic approaches for reconstructing gene regulatory networks.