From SOSwiki

Jump to: navigation, search

Kevin Oishi

I was a graduate research assistant in the Self Organizing Systems / Synthetic Biology lab at the University of Washington. Starting March 10, I will be a Postdoctoral Research Scientist at the Institute for Disease Modeling at Intellectual Ventures Labs. I'm always happy to discuss research projects, feel free to contact me if you have any questions.

Kevin Oishi @ Google Scholar
Email: k oishi at u double-u dot e dee u
Curriculum vitae: cv.pdf

Education

Ph.D. Electrical Engineering, Department of Electrical Engineering, University of Washington, 2014.
| Self-Organizing Systems / Synthetic Biology Lab
M.S. Robotics, Robotics Institute, Carnegie Mellon University, 2006.
B.S. Computer Science, School of Computer Science, Carnegie Mellon University, 2004.
B.S. Mathematics (Discrete Math and Logic), School of Science, Carnegie Mellon University, 2004.

Research

Synthetic Biology
Self Organizing Systems
Distributed Systems and Algorithms
Graphical Models
Robotics and Automation

Ph.D. Work

Dissertation

Programming Molecules and Cells: Design Architectures for Chemical Reaction and Gene Regulatory Networks. Submitted March 7, 2014.
Committee members: Eric Klavins (Chair), Georg Seelig, James Carothers, Mark Oskin (GSR)

Thesis Defense

Programming Molecules and Cells: Design Architectures for Chemical Reaction and Gene Regulatory Networks
Programming Molecules and Cells: Design Architectures for Chemical Reaction and Gene Regulatory Networks

Programming Molecules and Cells: Design Architectures for Chemical Reaction and Gene Regulatory Networks. December 5, 2013. [pdf|movie1|movie2|supplemental]
Committee members: Eric Klavins (Chair), Georg Seelig, James Carothers, Mark Oskin (GSR)

Thesis Proposal

Programming Molecules and Cells: Design Architectures for Chemical Reaction and Gene Regulatory Networks. January 16, 2013.

Computation in Cells and Growing Microcolonies

A Framework for Implementing Finite State Machines in Gene Regulatory Networks
A Framework for Implementing Finite State Machines in Gene Regulatory Networks

Finite state machines are fundamental computing devices at the core of many models of computation. In biology, finite state machines are commonly used as models of development in multicellular organisms. However, it remains unclear to what extent cells can remember state, how they can transition from one state to another reliably, and whether the existing parts available to the synthetic biologist are sufficient to implement prespecified finite state machines in living cells. Furthermore, how complex multicellular behaviors can be realized by multiple cells coordinating their states with signaling, growth, and division is not well understood. I describe a method by which any finite state machine can be built using nothing more than a suitably engineered network of readily available repressing transcription factors. In particular, I show the mathematical equivalence of finite state machines with a Boolean model of gene regulatory networks. I describe how such networks can be realized with a small class of promoters and transcription factors. To demonstrate the robustness of our approach, I show that the behavior of the ideal Boolean network model approximates a more realistic delay differential equation model of gene expression. Finally, I explore a framework for the design of more complex systems via an example, synthetic bacterial microcolony edge detection, that illustrates how finite state machines could be used together with cell signaling to construct novel multicellular behaviors.

Simulating and Specifying Multicellular Behaviors

gro: Specification and Programming of Multi-celled Behavior
gro: Specification and Programming of Multi-celled Behavior

In collaboration with S. Jang, R. Egbert, and E. Klavins.

Recent advances in the design and construction of synthetic multicelled systems in E. coli and S. cerevisiae suggest that it may be possible to implement sophisticated distributed algorithms with these relatively simple organisms. However, existing design frameworks for synthetic biology do not account for the unique morphologies of growing microcolonies, the interaction of gene circuits with the spatial diffusion of molecular signals, or the relationship between multicelled systems and parallel algorithms. We developed gro, a framework for specifying and simulating multicellular behaviors that uses a simple 2D simulation of microcolony growth and molecular signaling. The framework allows the researcher to explore the collective behaviors induced by high level descriptions of individual cell behaviors.

DNA Programming

A biomolecular implementation of linear I/O systems
A biomolecular implementation of linear I/O systems

Linear I/O systems are a fundamental tool in systems theory, and have been used to design complex circuits and control systems in a variety of settings. Here I present a principled design method for implementing arbitrary linear I/O systems with biochemical reactions. This method relies on two levels of abstraction: first, an implementation of linear I/O systems using idealized chemical reactions, and second, an approximate implementation of the ideal chemical reactions with enzyme-free, entropy-driven DNA reactions. The ideal linear dynamics are shown to be closely approximated by the chemical reactions model and the DNA implementation. I illustrate the approach with integration, gain and summation as well as with the ubiquitous robust proportional-integral controller.

Masters Thesis

Stability and Control for a Class of Dynamic Legged Climbers, May 2006.

Stability and Control for a Class of Dynamic Legged Climbers
Stability and Control for a Class of Dynamic Legged Climbers

Motivated by the success of the lateral leg spring (LLS) and spring-loaded inverted pendulum (SLIP) templates for transverse and sagittal plane running on horizontal surfaces, my effort is to similarly approximate the analytically intractable dynamics of a full dimensional system through planar models, and develop simple control strategies based on analysis of these approximations. In this report I introduce low-dimensional generalizations of the LLS and SLIP templates capable of ascending and descending by considering configurations of the center of pressure outside of the set of asymptotically stable configurations in the horizontal plane, and allow a thrust phase to add or remove energy from the hopper. I provide mathematical analysis of these models where possible, and introduce approximate models and empirical data where analytical analysis is intractable. Stable control strategies developed from these low dimensional templates and approximations are demonstrated through simulation.

Past Research and Other Projects

2005, Linear and Nonlinear Dimensionality Reduction in fMRI Data for Picture-Sentence Classification (with Stuart Anderson).
2002-2004, Urban Search and Rescue: Cyber Agents, Robots and People (advisors Illah Nourbakhsh, Katia Sycara, Mike Lewis).
2004, Development of an Automatic Bicycle Shifting System and Associated Human Interfaces (with Stuart Anderson and Michael Blain).

Publications

Kevin Oishi @ Google Scholar

Recent Journal Publications

  1. K. Oishi and E. Klavins, Framework for Implementing Finite State Machines in Gene Regulatory Networks, ACS Synthetic Biology, February 21. 2014. url
  2. S.S. Jang, K.T. Oishi, R.G. Egbert, and E. Klavins, Specification and simulation of multicelled behaviors, ACS Synthetic Biology, Vol. 1, No. 8, pp. 365--374. 2012. url
  3. K. Oishi and E. Klavins, A biomolecular implementation of linear I/O systems, IET Systems Biology, July 2011, vol 5, no. 4, p.252–260. url (IET), url (IEEE Xplore), Supplementary Material

Conference Abstracts and Posters

  1. K. Oishi, E. Klavins, Finite State Machines and Turing Universal Computation in Cells. SB6.0 (6th International Meeting on Synthetic Biology), 2013. url
  2. K. Oishi, S.S. Jang, R. Egbert, E. Klavins, gro: Specification and Programming of Multi-celled Behavior. q-bio, 2012. Poster + Abstract. url
  3. S.S. Jang, K.A. Havens, J.M. Guseman, E. Pierre-Jerome, N. Bolton, B.L. Moss, K. Oishi, Y. Yang, M. Gardner, T. Gu, J.L. Nemhauser, E. Klavins, Engineering with auxin: characterization of a synthetic signal processing toolbox. q-bio, 2012. Poster + Abstract. url
  4. J. Bishop, K. Oishi, E. Klavins, Feedback-regulated RNA fuel for DNA circuits. DNA17 (17th International Conference on DNA Computing and Molecular Programming), 2011. Poster + Abstract. Best Poster Award.
  5. K. Oishi, Y. Chen, E. Klavins, Implementing Autonomous Linear Systems with DNA. DNA17 (17th International Conference on DNA Computing and Molecular Programming), 2011. Poster + Abstract.

Invited Talks and Presentations

December 14, 2013, A Framework for Implementing Finite State Machines in Gene Regulatory Networks. 2013 Molecular Programming Project Workshop, Oxnard, California.
March 29, 2013, Implementing Finite State Machines with Gene Regulatory Networks. Theorizza (=Theory + Pizza), University of California, San Francisco.
January 11, 2013, Programming Molecules and Cells: Design Architectures for Chemical Reaction and Gene Regulatory Networks. Thesis Proposal, University of Washington.
January 21, 2011, Using See-Saw Gates and Linear Systems to Implement an Oscillator. Molecular Programming Project Supergroup Meeting, University of Washington, broadcast at Caltech New Media Classroom.
January 9, 2009, Approximating linear systems with DNA reactions. 2009 Molecular Programming Project Workshop, Oxnard, California.
May 11, 2006, Stability and Control for a Class of Dynamic Legged Climbers. Foundations of Robotics Seminar, Carnegie Mellon University.

Teaching

Teaching, Guest Lectures

Winter 2014, Teaching Assistant. Molecular and Neural Computation (CSE P 590), University of Washington. Course Instructor: Georg Seelig.
Spring 2013, Guest Lecturer. Unconventional Computing (EE 590), University of Washington. Course Instructor: Eric Klavins.
Autumn 2012, Teaching Assistant. Introduction to Synthetic Biology (BioE 423/523, CSE 486/586, EE 423/523), University of Washington. Course Instructor: Eric Klavins.
Spring 2009, Guest Lecturer. BioCircuits (EE 500/546), University of Washington. Course Instructor: Eric Klavins.
Autumn 2009, Teaching Assistant. Introduction to Synthetic Biology (BioE 498/599, CSE490/599, EE 400/546), University of Washington. Course Instructor: Georg Seelig.
Winter 2008, Teaching Assistant. Operating Systems (CSE 451), University of Washington. Course Instructor: Andrew Whitaker.
Autumn 2007, Teaching Assistant. Introduction to Computer-Communication Networks (CSE 461), University of Washington. Course Instructor: John Zahorjan.

Reading Group

2010, Concurrency Reading Group. Fridays at 10:30am, EE437.

Other Projects and Links

Calendar | Old CMU web page