Implementation of a virtual environment system based on geographical information system and environmental models

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.Includes bibliographical references (p. 162-165).by Chen-Hsiang Yeang.M.S

Local governments and information systems in rural Thailand

Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 1998.Includes bibliographical references (p. 125-128).by Chen-Hsiang Yeang.M.C.P

Distributed GIS for Monitoring and Modeling Urban Air Quality

The progress of technology has made the measurement of air quality and the simulation of complex air pollution models both feasible and cost-effective. However, there is a long way to go in terms of facilitating widespread access to the data and models, and linking the monitoring of trace gases with specific urban activities and land use that might be controllable. As part of a NASA-funded project, we are working with scientists and engineers to design and test a distributed GIS infrastructure for studying such "urban respiration" phenomena. Measurements of trace gases within a metropolitan area (from mobile and fixed instruments) are geo-referenced, time-stamped, and stored in a relational database server (Oracle). GIS services (using ArcInfo and ArcView) are connected to the database so that subsets of the trace gas measurements can be extracted and converted on-the-fly into GIS data layers. These subsets (by location, date, and time-of-day) can be displayed and cross-referenced with other layers such as weather conditions, land use and cover, topography, hydrography, demography, and congestion levels of road networks. A web-based interface (using ArcView Internet Map Server) allows research team members at different locations to query, visualize, and process the cross-referenced data layers in order to generate surface level estimates of initial conditions for use in the air quality models.NAS

Inferring regulatory networks from multiple sources of genomic data

Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.Includes bibliographical references (p. 279-299).(cont.) algorithm to identify the regulatory models from protein-DNA binding and gene expression data. These models to a large extent agree with the knowledge of gene regulation pertaining to the corresponding regulators. The three works in this thesis provide a framework of modeling gene regulatory networks.This thesis addresses the problems of modeling the gene regulatory system from multiple sources of large-scale datasets. In the first part, we develop a computational framework of building and validating simple, mechanistic models of gene regulation from multiple sources of data. These models, which we call physical network models, annotate the network of molecular interactions with several types of attributes (variables). We associate model attributes with physical interaction and knock-out gene expression data according to the confidence measures of data and the hypothesis that gene regulation is achieved via molecular interaction cascades. By applying standard model inference algorithms, we are able to obtain the configurations of model attributes which optimally fit the data. Because existing datasets do not provide sufficient constraints to the models, there are many optimal configurations which fit the data equally well. In the second part, we develop an information theoretic score to measure the expected capacity of new knock-out experiments in terms of reducing the model uncertainty. We collaborate with biologists to perform suggested knock-out experiments and analyze the data. The results indicate that we can reduce model uncertainty by incorporating new data. The first two parts focus on the regulatory effects along single pathways. In the third part, we consider the combinatorial effects of multiple transcription factors on transcription control. We simplify the problem by characterizing a combinatorial function of multiple regulators in terms of the properties of single regulators: the function of a regulator and its direction of effectiveness. With this characterization, we develop an incrementalby Chen-Hsiang Yeang.Sc.D

DNA Binding and Games

We propose a game-theoretic approach tolearn and predict coordinate binding of multiple DNA bindingregulators. The framework implements resource constrainedallocation of proteins to local neighborhoods as well as to sitesthemselves, and explicates coordinate and competitive bindingrelations among proteins with affinity to the site or region. The focus of this paper is on mathematical foundationsof the new modeling approach. We demonstrate the approachin the context of the lambda-phage switch, a well-known biologicalsubsystem, and provide simulation results that successfully illustrate the predictions that can be derived from the modelwith known structure and affinities. Subsequentwork will elaborate on methods for learning the affinities and gamestructures from available binding data