A heterogeneous framework for reasoning about immunological scenarios /
medicine for many years. However, limited success has
| Main Author: | |
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| Format: | Thesis Book |
| Language: | English |
| Published: |
[Place of publication not identified] :
[publisher not identified] ;
1994.
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| Subjects: | |
| Online Access: | http://proxy.library.tamu.edu/login?url=http://proquest.umi.com/pqdweb?did=741966021&sid=1&Fmt=2&clientId=2945&RQT=309&VName=PQD |
| Summary: | medicine for many years. However, limited success has prompted the development of systems capable of deep reasoning. The immune system is quite complex, yet current research has provided detailed knowledge concerning the immune response. However, limitations imposed on laboratory study by the distributed nature of the immune system make it an excellent candidate for study via deep models. This research presents a model for understanding cefl/cytokine interactions in the immune system, stating expected behavior and comparing the expectations to actual data. An overview of basic immunological knowledge used in the construction of the system (IMMSIM) is presented. A multi-layered heterogeneous knowledge representation framework called the immunological knowledge representation structure (IKRS) is introduced, modeling information at the molecular, cellular and systemic levels. The concepts of events and activities are introduced in order to use the IKRS to generate expected scenarios concerning what will occur given some set of events that befall the immune system. The heterogeneity of the system is further enhanced by developing its capability to numerically model the scenarios. Finally, methods for comparing expected scenarios with actual data and explaining differences found therein are presented. |
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| Item Description: | Vita. "Major Subject: Computer Science". |
| Physical Description: | ix, 123 leaves : illustrations ; 28 cm. Issued also on microfiche from University Microfilms Inc. |
| Bibliography: | Includes bibliographical references. |