Research on gene-based drug toxicity research framework : motifs and regulation relationship discovery based on fuzzy clustering

Pao Yue-kong Library Electronic Theses Database

Research on gene-based drug toxicity research framework : motifs and regulation relationship discovery based on fuzzy clustering

 

Author: Dong, Xiaofeng
Title: Research on gene-based drug toxicity research framework : motifs and regulation relationship discovery based on fuzzy clustering
Degree: M.Sc.
Year: 2009
Subject: Hong Kong Polytechnic University -- Dissertations.
Gene therapy.
Cellular control mechanisms.
Drugs -- Toxicology.
Department: Dept. of Computing
Pages: 152 p. : col. ill. ; 30 cm.
Language: English
InnoPac Record: http://library.polyu.edu.hk/record=b2303069
URI: http://theses.lib.polyu.edu.hk/handle/200/4226
Abstract: In post genome era, system biology and bio-pharmaceuticals got rapid development in the world. Lots of famous research institutes offered different courses. The rampart between fields has been broken. Medical scientist, biochemist, mathematician, and computer scientist merged each other. They work for a single goal: the system biology research. Gene therapy technique is becoming more and more accepted in the past few years. Gene-based drugs can be potentially used in clinical practice for treating genetic diseases before actual implementation of gene-based drug. Potential risks to patients should be thoroughly studied. This thesis devoted to study the framework of Gene-based drug toxicity. Major contributions are listed below. 1. Regulation network of dynamic equilibrium Generally, organism regulation networks are in equilibrium state. And regulation network and expression network products are in normal value area. Gene deviations in organism lead to disease. These deviations arise is due to environment changes. The reasons maybe include virus, bacteria, and other factors such as chemicals, temperature or radiation that can influence the cell environment. Drug treatment aims at keeping regulation network to be normal expression levels even after stopping the drug. Some diseases have origins in genetic materials, thus normal chemical drugs can hardly have effects. Specifically, normal chemical drugs or Chinese drugs can't target at special genes. Gene-based drugs can target genetic materials thus making it possible to treating genetic diseases. Drug gene sessions merged with cell-self gene, and then get new dynamic equilibrium status. The effect of the drug will be directly reflected in cells expression networks products. 2. Definition of gene based "Toxicity" Definition: The Toxicity of drug is the effect of drug. As above discussion, that means the drug is useful if it can make gene regulation network recovering to normal status. Otherwise the drug is useless. Toxicity has two meanings: a) "Toxicity" is defined by its effect. Just against cell living change is identified "Toxic". If the drug do not make regulation network worse, it is innoxious generally. b) "Toxicity" is a relative concept. Some toxic material may make cell regulation network back to normal status, while some non-toxic material may make cell regulation network abnormal. 3. Construct the research framework of toxicity theory of Gene-based drug As discussed above, gene-based drugs influence gene regulation network through common regulation and intermediate expression products. There are two types of toxicity of gene-based drugs: a) Make network producing against expression products. This against effect can be handled through analyzing expression products; b) Make genome change. This change can be directly handled through analyzing sequence or indirectly handled through analyzing its expression products. We proposed a computing framework of toxicity research. The proposed approach has three stages. More details will be discussed later. In organism regulation network, the equilibrium status is dynamic. The channel of regulatory factor, intensity of signal and the change of regulatory element are all dynamic. So, it is the base work that reconstruct dynamic regulation network. Therefore, reconstructing the dynamic regulation network is the base of this study. This thesis focused on the key problems of reconstructing the regulation as well as the implementation algorithms of motif and regulation relationship. 4. Fuzzy clustering algorithm Clustering approach has been widely used in many areas. In this thesis, we will discuss clustering approaches that utilizing fuzzy set distribution characteristics. An algorithm of fuzzy c-means approach will be specifically implemented. 5. Approach of drug toxicity computation As one major task of this thesis, we present one computing formula to compute the drug toxicity: In this formula, V is the virulence, m is halt-life of drug. 6. Thinking of FRM (Fuzzy relevance means clustering) Because of the methods of general distance lose relevance knowledge, so the effective improvement is hardly. We proposed the thinking of FRM, and will discuss it in future. It is the main mechanism that external genes could co-regulate with Endogenous genes. This thesis studied the influencing relationship of gene-based drugs and genes of breast cancer. Co-regulation rate and relationship rate are introduced to measure the influencing effect.

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