1. Bio-Computation DARPA/ITO Sri Kumar
I am Sri Kumar, Program Manager in ITO of DARPA.
Bio-Comp is one of the new programs at DARPA, which I am managing.
I will talk about this program:
The genesis
Goals and Challenges
IA relatiponships
DARPA/ITO
Sri Kumar

2. Background Opportunities at INFO: BIO: MICRO/NANO Intersection?
IT in driver seat; FY 00
Synthesis of several ideas: Seedlings
DNA Computing
Wet Computer: Beyond Silicon?
LISP model (cut, paste, recursion); Massive Parallelism (Adelman 94)
Wet information storage? Billion Terabits in a gram!
Algorithms driving synthetic DNA Nano-structures?
Natural Computation in Cells
Cell Models and Bio-SPICE
Lambda Phage, Caulobacter Cell Cycle
Characterize, Predict, and Control, processes of interest to DOD
Lessons from Bio to IT
Pathogenic Processes. CBW
Rhythms. War fighter effectiveness in stress
Bio-sensors; Enhanced DNA Computing

3. Bio-Computation: Program
DNA Computation
Information processing using bio-molecular coding and manipulation
Leverage massive parallelism
Solution to complex problems
Content addressable storage
Nano-structures
Harvest Nature’s Tool Chest
Models of Conserved Mechanisms
Natural Computation
Develop Cell Models/Bio-Spice
Techniques and tools for Intra-cell analysis
Models of intra-cellular processes
Regulatory mechanisms
Gene-protein interactions
DNA Editing In-Vivo
Circadian Rhythms
Piliation
Sporulation
Asymmetric Division
Chemotaxis
Cell Cycle
Bio-Molecular and Cellular Level computational mechanisms and models

4. AREA 1: Topic 1 Scalable DNA COMPUTING
DNA, RNA, other Nucleotides
Leap beyond toy problems
3-SAT, 6 variable
Scaling
Coding. Bit -> nt
Automation of manual tasks; micro-fluidic devices
Prototypes

5. AREA 1: Topic 2 Content Addressable Storage
A gram of DNA can store Terra- bytes
R&D Leading to
System Development
Tagged DNA: address
Error Resiliency
High Speed I/O
Prototype Development

6. AREA 1: Topic 3 Programmable Nano-structures
Demonstrate techniques for producing
Self-assembled, computationally
driven DNA Structures
2-D, 3-D
Application Demonstrations: Examples
Cages for Crystallography
Layout for Molecular Electronics/ Q-dots
Precision features: 10s of nm
12.6 nm
4 nm

7. Area 1: Topic 4 Synthetic Bio-Circuits
Design multi-state switching elements and gates to instrument/control cell dynamics
Flip-Flops, Oscillators
Control Applications
Record Events
Conditional gene response
Switches Today
RS Latch 2- state (2000)
From 2-3 (current) to 16+states
4 latches in cascade, plus gates
Technical Challenges
Monitored state -> signal
Identifying the gene network
Insulated operation
Heritability, speed,
Long-Oligos needed
Clock (2000)

8. SIMULATION PROGRAM FOR INTRA-CELL EVALUATION
Technical Area 2: Computational Models of Intra-Cell Processes, and Systems
Develop Bio-SPICE
SIMULATION PROGRAM FOR INTRA-CELL EVALUATION
Tool: In Silico Analysis
SPATIO-TEMPORAL Models
Capturing interactions in the network of Gene-protein interactions

9. Area 2: Research Topics Model Kernel Experimental Validation
Simulation Environment
Software Integration

10. Area 2: Topic 1 Models Spatio-Temporal Models
Reaction/Diffusion
Deterministic, Stochastic
Analog, Discrete, Asynchronous
Transport, Compartmental…
Multi-Scale, Multi-resolution Models
Time (msecs to hours)
Size (few to large – gene/proteins)
Analytical Tools
Stability, Bifurcation
Phenomenological models
Model fitting from uncertain data

11. Area 2: Topic 2 Experimental Validation
EXAMPLES, not LIMITED TO:
DNA Editing In-Vivo
Circadian Rhythms
Piliation
Sporulation
Secretion
Asymmetric Division
Cell Cycle
……….
B.subtilis
Piliation
Ciliate Editing

12. Area 2: Topic 3 Simulation Environment
Parallel Simulation to gain speed
Biologist Friendly
GUI
Data Visualization
Easily programmable
High Level Language and compilation
Data basing tools:
access, query
Local, remote, distributed environment
Operating environment
Efficiently manage all components
Platform independence

13. Area 2: Topic 4 Software Integration
Issues
Develop open architecture, working with the community
Controlling Revisions and Repository
Expert panel
Revision (1-2 times per yr)
Software Integration and Revisions
Version Control, Model evaluations
Team for software integration
Committed to open source development
Strong technical expertise, all-aspects

14. Bio-Spice: Open Source
Adopt Open Source Model, Multiple Developers/Users
Continual testing, debugging, augmenting by community
Reliable models of complex systems
Robust, widely accepted tools and techniques
Models of Success: SPICE, UNIX, GNU, LINUX, TeX etc.

15. OS Licensing Models: Today
Public Domain: (e.g., Spice) No license, free
BSD (university; e.g., Unix)
Right for unlimited use; unrestricted derivative works (could be proprietary)
Developers copyright retained
Optional: Ack original source (advertising)
No liability. Optional: software provided at cost
Environment: publish for credit. Outsiders can harvest
GPL (GNU Public License; FSF. e.g., Emacs, Linux, TeX)
Designed to prevent open source to create proprietary works
Modifications inherit GPL; distribute ‘openly’ without fee
Artistic PL (Software Developers. e.g., Ada, Perl)
Non-open modifications only for internal use, not for external distribution
Encourages code sharing more than BSD, less restrictive than GPL
Mozilla PL; NPL: (Commercial. e.g., Netscape)
Modifications to open original must be open (similar to GNU)
Can be combined with separate proprietary program. Clear open/closed boundary
Can be licensed for a fee; need not be made publicly avalible
Separation between open and closed must be explicit at boundaries

16. Bio-Spice Licensing Developer/User Community
All have same right to use, modify, distribute released versions within community
Baseline open. All derived works will remain open
Revision, enhancement, modification, translation, abridge, expansion
Can be linked to other proprietary software and proprietary data and commercialized
Data from open literature/database remains open.
Integrator to execute license

17. Bio-Comp: Inter-Agency Coordination
DARPA, NSF, and NIH..
DARPA Focus: Molecular and cellular basis for pathogenesis, war fighter stress, rhythms and performance, synthetic DNA computations for complex problems.
NSF Focus: Basic Science
NIH Focus: Health and Medicine
DARPA-ITO/NSF-CISE Memorandum of Agreement (MOA) on Bio-Computation (May 2001): DNA Computing and Bio-SPICE.
DARPA/NIH coordination under discussion.