IMPROVED NON-LINEAR MODELING

Award Information
Agency:
Department of Health and Human Services
Branch
n/a
Amount:
$200,000.00
Award Year:
2002
Program:
SBIR
Phase:
Phase I
Contract:
1R43CA094450-01
Agency Tracking Number:
CA094450
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
AISN SOFTWARE
AISN SOFTWARE, BOX 449, 11829 E MAPLETON RD, MAPLETON, OR, 97453
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
RONALD BROWN
(541) 268-1953
RONB@PRESYS.COM
Business Contact:
RON BROWN
(541) 268-1954
RONB@PRESYS.COM / REBROWN@HIWAAY.NET
Research Institution:
n/a
Abstract
Dose-response, enzyme kinetics, and other data in the biosciences are often modeled using non-linear least-squares curve-fitting algorithms. These methods are adversely impacted both by outliers and a non- Gaussian error distribution. Misleading confidence intervals on crucial parameters can result. This proposal describes preliminary non-linear optimization technology in the areas of robust fitting and bootstrapping that have shown the ability to substantially improve the accuracy and reliability of biomodeling. Funding is sought for the optimization of the analytic algorithms and the development of the software technology necessary to add these methods to an established commercial software product. Funding is also sought for the support of extensive analysis experiments with both real-world data and Monte-Carlo simulations. In addition to making the innovation available in commercial software, this project will enable the thorough research and development necessary for peer-reviewed publication of these methods. A Phase II project is envisioned which includes extending the robust fitting innovations of Phase I in order to achieve the true maximum-likelihood optimization adaptively, based on the use of a non-linear optimization merit function that adapts to actual experimental error distribution.

* information listed above is at the time of submission.

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