Avtor/Urednik		Hristovski, Dimitar
Naslov		Odkrivanje genetskih zakonitosti iz biomedicinskih podatkov
Tip		monografija
Kraj izdaje		Ljubljana
Založnik		Medicinska fakulteta
Leto izdaje		2000
Obseg		str. 65
Jezik		slo
Abstrakt		Background: The number and the size of the databases, which are important for the field of genetics, are very large. This is especially true for the human genome research. Various international projects produce data in enormous quantities. In the field of genetics, there is a noticeable gap between the speed of producing new data and the ability of the researchers to analyse the data and synthesise it into new knowledge. Because of that, there is an urgent need in genetics for new methods and tools for knowledge discovery in databases. Methods and materials: In this PhD thesis, we developed new methodology for genetic knowledge discovery in biomedical databases.This methodology served as a basis upon which in the first part of the thesis we developed an interactive genetic knowledge discovery support system (SPOGZ), which is general enough to be used in other medical domains as well. The goal of the system is: for a given starting concept of interest, discover new, potentially meaningful relations with other concepts that have not been published in the medical literature before. The main idea is to first find all the concepts Y related to the starting concept X (e.g. if X is a disease then Y can be pathological functions, symptoms, ...). Then all the concepts Z related to Y are found (e.g. if Y is a pathological function, Z can be a chemical regulating that function or a molecule, structurally or functionally, related to the pathophisiology): As a last step we check if X and Z appear together in the medical literature. If they do not appear together then we have discovered a potentially new relation between X and Z. This relation should be confirmed or rejected using human judgement, laboratory methods or clinical investigations, depending on the nature of X and Z. The known relations between the medical concepts come from the Medline bibliographic database. (Abstract truncated at 2000 characters).
Deskriptorji		MEDLINE VOCABULARY, CONTROLLED UNIFIED MEDICAL LANGUAGE SYSTEM DECISION TREES CLUSTER ANALYSIS INFORMATION STORAGE AND RETRIEVAL USER-COMPUTER INTERFACE SUBJECT HEADINGS Y CHROMOSOME INFERTILITY, MALE CHROMOSOME DELETION PHENOTYPE INCONTINENTIA PIGMENTI