CONFERENCE: Cold Spring Harbor Laboratory Synthetic Biology Course-July 27-August 10, 2015

Cold Spring Harbor Laboratory, Cold Spg Hbr NY

Investigators

Abstract

Synthetic biology is a rapidly expanding multi-disciplinary research area that relies on the integration of expertise in biology, engineering, mathematics, chemistry, and physics. This field uses theoretical and engineering principles to advance fundamental biological understanding and develop bio-inspired products. The challenge of synthetic biology today is that interdisciplinary expertise is often minimal, whereas a basic comprehension of the various underlying fields is crucial to foster successful collaborations. This course (July 27 - August 10, 2015) offered through the Cold Spring Harbor summer course educational program represents a significant effort to address this need. The series of lectures include laboratory exposure to cutting edge advances in experimental and theoretical synthetic biology. The course is structured to motivate the participants to share their knowledge with colleagues at their home institutions, which may inspire more broadly a systems and synthetic biology course and curriculum development. This course will help advance an emerging interdisciplinary science that, in addition to providing insights into the complexity of biology, will also inspire innovations that can provide critical solutions for many current and impending societal needs. The course fulfills an important need for development of an interdisciplinary research workforce that is more aware of the opportunities that can be realized from interdisciplinary collaborations including effective communication between students and experts. The teaching material includes cutting edge training in such areas as the theory and use of CRISPR technology to alter the genome of complex biological systems; proficiency in cell-free transcription-translation (TX-TL) methods; rapid molecular cloning using the Golden Gate assembly method; and gaining fundamental understanding of computational biology using ordinary differential equations. In addition, the course will provide sessions to develop specific biosensors for metabolic engineering.