Maygen: A Symbolic Debugger Generation System

With the development of high-level languages for new computer architectures comes the need for appropriate debugging tools as well. One method for meeting this need would be to develop, from scratch, a symbolic debugger with the introduction of each new language implementation for any given architecture. This, however, seems to require unnecessary duplication of effort among developers. This paper describes Maygen, a "debugger generation system," designed to efficiently provide the desired language-dependent and architecture-dependent debuggers. A prototype of the Maygen system has been implemented and is able to handle the semantically different languages of C and OPAL.

The Kineticist's Workbench: Combining Symbolic and Numerical Methods in the Simulation of Chemical Reaction Mechanisms

The Kineticist's Workbench is a program that simulates chemical reaction mechanisms by predicting, generating, and interpreting numerical data. Prior to simulation, it analyzes a given mechanism to predict that mechanism's behavior; it then simulates the mechanism numerically; and afterward, it interprets and summarizes the data it has generated. In performing these tasks, the Workbench uses a variety of techniques: graph- theoretic algorithms (for analyzing mechanisms), traditional numerical simulation methods, and algorithms that examine simulation results and reinterpret them in qualitative terms. The Workbench thus serves as a prototype for a new class of scientific computational tools---tools that provide symbiotic collaborations between qualitative and quantitative methods.

Protein Microarray: "Theory" to "Real Practice"

Fueled by ever-growing genomic information and rapid developments of proteomics–the large scale analysis of proteins and mapping its functional role has become one of the most important disciplines for characterizing complex cell function. For building functional linkages between the biomolecules, and for providing insight into the mechanisms of biological processes, last decade witnessed the exploration of combinatorial and chip technology for the detection of bimolecules in a high throughput and spatially addressable fashion. Among the various techniques developed, the protein chip technology has been rapid. Recently we demonstrated a new platform called “Spacially addressable protein array” (SAPA) to profile the ligand receptor interactions. To optimize the platform, the present study investigated various parameters such as the surface chemistry and role of additives for achieving high density and high-throughput detection with minimal nonspecific protein adsorption. In summary the present poster will address some of the critical challenges in protein micro array technology and the process of fine tuning to achieve the optimum system for solving real biological problems.