Niles A. Pierce is the MacArthur Professor of Applied & Computational Mathematics and Bioengineering and Executive Officer for Biology & Biological Engineering at the California Institute of Technology. A co-founder of the fields of dynamic nucleic acid nanotechnology and molecular programming, his research interests include the development of mathematically rigorous, physically sound, computationally efficient algorithms for the analysis and design of nucleic acid systems, and the development of dynamic nucleic acid nanotechnologies for imaging the molecules of life, for instrument-free at-home pathogen detection, and for cell-selective treatment of disease using small conditional RNAs (scRNAs). Professor Pierce joined the Caltech faculty in 2000 and was awarded the Institute’s Richard P. Feynman Prize for Excellence in Teaching in 2003. His honors include the Fox Prize in Numerical Analysis, a National Science Foundation CAREER Award, and the Rozenberg Tulip Award, which recognizes outstanding career achievement in molecular programming. He has also been named a Guggenheim Fellow and the 74th Eastman Visiting Professor at the University of Oxford. He graduated as valedictorian from Princeton University with a BSE in Mechanical & Aerospace Engineering and completed a DPhil in Applied Mathematics as a Rhodes Scholar at the University of Oxford.

Keynote Abstract

NUPACK: Analysis and Design of Nucleic Acid Structures, Devices, and Systems

NUPACK is a growing software suite for the analysis and design of nucleic acid structures, devices, and systems, serving researchers in the emerging disciplines of molecular programming, nucleic acid nanotechnology, synthetic biology, and across the life sciences. NUPACK algorithms have pioneered the treatment of complex and test tube ensembles containing arbitrary numbers of interacting strand species, providing crucial tools for capturing concentration effects essential to analyzing and designing intermolecular interactions that are a hallmark of these fields. To enable reaction pathway engineering of dynamic hybridization cascades or large-scale structural engineering including pseudoknots, NUPACK generalizes these analysis and design capabilities to multi-tube ensembles. The all-new NUPACK 4 scientific code base offers enhanced physical models (coaxial and dangle stacking subensembles), dramatic speedups (20-120x for test tube analysis), increased scalability for large complexes (30,000 nt), mixed materials (RNA/DNA or RNA/2’OMe-RNA specified at nucleotide resolution), and diverse hard and soft sequence constraints for design. The all-new NUPACK cloud web app facilitates rapid job submission and result inspection with scientific algorithms running in parallel in the scalable NUPACK hybrid cloud.