全球有數以百萬計的人患有慢性皮膚疾病—牛皮癣。在2014年，世界衛生組織（WHO）將牛皮癣確定為嚴重的非傳染性疾病。在這項研究中，我們運用系統生物學的方法來探究牛皮癣的潛在病因，並識別潛在的藥物治療靶點。該研究運用大數據挖掘來構建候選的全基因組遺傳和表觀遺傳網絡（GWGEN）。隨後，我們應用系統順序檢測和系統識別方法，以識別在牛皮癣和非牛皮癣狀態下的真實GWGEN。利用主要網絡投影（PNP）方法提取核心GWGEN，並使用京都基因和基因組百科全書（KEGG）通路對相應的關鍵信號通路進行了註解。通過比較牛皮癣和非牛皮癣的關鍵信號通路及其下游的細胞異常，我們確定了NF-κB、STAT3、CEBPB和FOXO1作為重要的發病生物標記，並被認為是牛皮癣治療的藥物靶點。隨後，我們訓練了基於深度神經網絡的藥物-靶點互作模型，用於預測候選分子藥物。通過考慮足夠的敏感性、毒性和調控能力作為藥物設計規範，我們從候選分子藥物中選擇了柚皮素、芒柄花素和萜烯酸，將其結合成潛在的多分子藥物，用於牛皮癣的治療。

Psoriasis, a chronic skin condition, affects millions of individuals worldwide. In 2014, psoriasis was acknowledged as a severe non-communicable disease by the World Health Organization (WHO). In this study, we utilized a systems biology approach to investigate the underlying pathogenesis of psoriasis and identify potential drug targets for therapeutic treatment. The study conducting big data mining to construct a candidate genome-wide genetic and epigenetic network (GWGEN). Subsequently, we applied system order detection and system identification methods to identify real GWGENs in psoriatic and non-psoriatic conditions. Core GWGENs were extracted using the Principal Network Projection (PNP) method, and the corresponding key signaling pathways were annotated using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Through the comparison of key signaling pathways between psoriasis and non-psoriasis conditions and their downstream cellular abnormalities, NF-κB, STAT3, CEBPB, and FOXO1 were identified as significant biomarkers of pathogenesis and were considered to be drug targets for the therapeutic treatment of psoriasis. Then, DNN-based DTI model was trained to predict candidate molecular drugs. By considering adequate sensitivity, toxicity, and regulatory ability as drug design specifications, Naringin, Butein, and Betulinic acid were selected from the candidate molecular drugs and combined into potential multi-molecule drugs for the treatment of psoriasis.

摘要----I
Abstract----II
誌謝----III
Contents----IV
1.Introduction----1
2. Results----11
2.1 An overview of Systems Biology Approaches for the Study of Pathogenesis and Systematic Drug Design and Discovery for treating Psoriasis----11
2.2. The key Signaling Pathways and Associated Cellular Dysfunctions for Investigating the Molecular Pathogenesis of Psoriasis----14
2.3 The Specific Molecular Pathogenesis of Non-Psoriasis ----18
2.4. Design and Discovery of Potential Multi-Molecular drugs for treatment of psoriasis by Drug Design Specifications and Deep Neural Network-Based Drug-Target Interaction Model----18
3. Discussion ----25
4. Materials and Methods ----27
4.1 A Overview of the process of constructing core Genome-Wide Genetic and Epigenetic Networks (GWGENs) for both psoriasis and non-psoriasis----26
4.2 Data collection and preprocessing of microarray data and candidate GWGENs----28
4.3 Building the Stochastic System Models of Candidate GWGEN----29
4.4 System Order Detection Method and System Identification Scheme for Removing False Positives and Detecting Real GWGENs in Psoriasis and Non-Psoriasis----32
4.5 Extracting the Core GWGENs via Principal Network Projection (PNP) method from the Real GWGENs----37
4.6 Design and Discovery of Multi-Molecule Drug for Treatment of Psoriasis by DNN-Based DTI Model----40
5. Conclusions----43
Reference ----44

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