The overall goal of this project is to produce a hardware and software system for high-resolution (ca. 1 kb) DNA physical mapping, usable in a laboratory environment by a technician with no formal computer science background, This system will be applicable in a variety of DNA mapping environments, including mapping involving the human genome and the genomes of other higher organisms. It will be targeted to YAC technology and top- down mapping strategies.
The specific aims are to: 1) develop data structures for manipulating and processing DNA restriction maps, starting with raw data and proceeding through the development of completed maps; 2) design and implement a computational database to be used as a repository of this date; 3) develop and implement a variety of algorithms for performing DNA mapping; 4) create an interactive editing system for creating and manipulating DNA restriction maps; and 5) integrate these and other components into a hardware and software DNA mapping system, usable in a biological laboratory by technical personnel untraned in computer science. The software will be designed with portability in mind, the final product being composed entirely of C code, supported only by SYBASE and X Windows. The software architecture will be """"""""open"""""""" so that the incorporation of new mapping algorithms will not be an arduous task. The human interface to the system will include textual input, interactive menu control, graphical map display, and gel image display. The system will focus on clone-overlap mapping techniques and will constitute a software toolkit, providing multiple DNA mapping algorithms at three different levels of DNA mapping: clone ordering strategies, group boundary determination, and fragment order determination. The technicians will be able to select combinations of these algorithms to produce a mosaic of composite DNA mapping algorithms, adjusting to the specific mapping task. All of the algorithms will be cast within the framework of multiple- restriction-enzyme mapping. The framework allows fragment-size data from more than one restriction enzyme to be used, in order to reduce the uncertainty of clone overlap. In this framework, a linear increase in the experimental effort produces an exponential improvement in the quality of the maps produced.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project (R01)
Project #
3R01HG000180-04S1
Application #
2208599
Study Section
Special Emphasis Panel (SRC (B1))
Project Start
1990-09-01
Project End
1996-01-31
Budget Start
1994-09-01
Budget End
1996-01-31
Support Year
4
Fiscal Year
1994
Total Cost
Indirect Cost
Name
Washington University
Department
Biostatistics & Other Math Sci
Type
Schools of Engineering
DUNS #
062761671
City
Saint Louis
State
MO
Country
United States
Zip Code
63130