2014年6月26日 生物信息学相关知识进期学习汇报

差异表达基因
蛋白质组学 及相关生物学 意义的富集分析
络氨酸代谢 补体和凝血级联反应
通过细胞色素P450代谢的外源性化学物质
精氨酸和脯氨酸代谢 焦点粘连RC5, POLD1, AURKA, CDT1, BUB1B were selected as hub nodes as their connectivity degrees > 30.
GEO:高通量基因表达数据库
RMA (Robust Multiarray Average) method：全局归一化校正
KEGG pathway database：
KEGG(京都基因与基因组百科全书)是基因组破译方面的数据库。日本京都大学 生物信息学中心的Kanehisa实验室于1995年建立了生物信息学数据库KEGG。目 前国际公认权威数据库之一。 KEGG PATHWAY数据库是一个手工画的代谢通路的集合，包含以下几方面的分 子间相互作用和反应网络 ： 1.新陈代谢 2.遗传信息加工 3.环境信息加工 4.细胞过程 5.生物体系统 6.人类疾病 7.药物开发
The functional enrichment analysis of the DEGs
KEGG pathway database is a recognized and comprehensive database including all kinds of biochemistry pathways [17]. In this work, the KEGG database was applied to investigate the enrichment analysis of the DEGs to find the biochemistry pathways which might be involved in the occurrence and development of ovarian cancer. DAVID [18] was used to perform the KEGG pathway enrichment analysis with the p-value < 0.05 and gene count > 2.
Materials and methods
Data source
The gene expression profiles of GSE14407 which was contributed by Bowen, N.J., et al. [13] were obtained from National Center of Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database (http://www. /geo/). The platform of the GPL570 ([HGU133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array) was applied in the expression array. The datasets available in this analysis contained 24 samples, including 12 ovarian cancer samples and 12 controls. These data (CEL form) and annotation files were downloaded for further analysis.
Protein-protein interaction network construction（PPI）
Since proteins seldom perform their functions in isolation, it is important to understand the interaction of these proteins by studying larger functional groups of proteins [19]. In this study, the STRING online tools [20] were used to analyze the PPIs of the DEGs with the cut-off criterion of combined score > 0.4. The relationships of the nodes degree≤5 were abandoned, then the Cytoscape software was used to construct the network [21]. Form the previous study, most obtained PPI networks obeyed the scale-freeattribution [22]. So the node degree of the network was analyzed and used to obtain the hub protein in the PPI network. The node degree≥30 were selected as the threshold.
Vehicle（塑形剂） 饲养方法一： APAP（对乙酰氨基酚） 400mg/Kg
Vehicle（塑形剂）
48h
APAP（对乙酰氨基酚） 600mg/Kg
饲养方法二：
Vehicle（塑形剂）
APAP（对乙酰氨基酚） 400mg/Kg
收集血浆、肝脏组织 2h 4h 8h 12h 24h 48h
Vehicle（塑形剂） 饲养方法三： APAP（对乙酰氨基酚） 400mg/Kg
Identification of DEGs
After obtaining the raw data, the RMA (Robust Multiarray Average) method [14] of the R software [15] was used to perform quartile data normalization, then the t test methods of the Limma package [16] was used to identify DEGs. Values of |log Fold Change (FC)| > 2.0 and p-value < 0.05 were selected as the cut-off criteria.
生物信息学相关知识 进期学习汇报
在小鼠对乙酰氨基酚肝毒性耐受模型中基因表达的变化分析
2014年发表在《Toxicology and Applied Pharmacology》
《应用毒理学和药理学》杂志 2013年影响因子：3.975
Dosing regimen 1: Following overnight fast, mice were treated with APAP (400 mg/kg) in 50% propylene glycol or vehicle; then, 48 h later, APAP and vehicle pretreated animals were treated with either APAP (600 mg/kg) in 50% propylene glycol or vehicle (5 mL/kg i.p.). Liver and plasma were collected 4 or 24 h later. Dosing regimen 2: Following overnight fast, mice were treated with APAP (400mg/kg) in 50% propylene glycol or vehicle (5mL/kgi.p.). Liver and plasma were collected 2, 4, 8, 12, 24 and 48 h later. Dosing regimen 3: Following overnight fast, mice were treated with APAP (400 mg/kg) in 50% propylene glycol or vehicle (5 mL/kg i.p.). To block compensatory hepatocyte proliferation, 2 mg/kg colchicine or vehicle (saline; 5 mL/kg i.p.) was given 24 and 49 h later. A second dose of APAP (600 mg/kg) or vehicle (50% propylene glycol, 5 mL/kg i.p.) was administered 48 h after the initial APAP dose. Plasma and livers were collected 24 h after the second dose of APAP.
(A) VV24 (B) AV24 (C) VA24 (D) AA24
肝小叶中央区着重染色
Vehicle（塑形剂） 饲养方法三： APAP（对乙酰氨基酚） 400mg/Kg
48 h
Vehicle（塑形剂） APAP（对乙酰氨基酚） 600mg/Kg
阻止肝细胞代偿性增生 24h及49h分别进行干预
Network module analysis of the ovary cancer
The nodes and edges of the PPI network were so complicate that we need to conduct the enrichment analysis using the ClusterONE Cytoscape plug-in [23]. Minimum size >5 and minimum density < 0.05 were the parameters before running the ClusterONE to disclose the enriched functional modules of the PPI network. We also performed the GO (gene ontology) functional enrichment analysis of the module genes to analyze the gene function in the molecule level. Furthermore, the best enriched module was performed KEGG pathway enrichment analysis using DAVID [18].