With user-generated content, anyone can De a content creator. This phenomenon has infinitely increased the amount of information circulated online, and it is beeoming harder to efficiently obtain required information....With user-generated content, anyone can De a content creator. This phenomenon has infinitely increased the amount of information circulated online, and it is beeoming harder to efficiently obtain required information. In this paper, we describe how natural language processing and text mining can be parallelized using Hadoop and Message Passing Interface. We propose a parallel web text mining platform that processes massive amounts data quickly and efficiently. Our web knowledge service platform is designed to collect information about the IT and telecommunications industries from the web and process this in-formation using natural language processing and data-mining techniques.展开更多
文摘目的构建p ET-29a-CD63-LEL重组质粒,诱导蛋白表达,鉴定表达产物并纯化蛋白,为后续研究CD63-LEL蛋白对人舌鳞癌侵袭转移的影响奠定基础。方法根据美国国立生物技术信息中心(NCBI)中查询到的CD63-LEL基因序列,运用RT-PCR技术从TCA-8113细胞中获得CD63-LEL的c DNA序列,经PCR、双酶切及测序确定获得p ET-29a-CD63-LEL重组载体后,转化至大肠埃希菌E.coli BL21(DE3)感受态中,通过异丙基硫代-β-D-半乳糖苷(isopropylthio-β-Dgalactoside,IPTG)诱导表达,运用镍柱亲和层析法纯化获得p ET-29a-CD63-LEL融合蛋白。结果成功构建了p ET-29aCD63-LEL重组质粒,经SDS-PAGE凝胶电泳检测:在37℃,1 mmol/L IPTG诱导12 h p ET-29a-CD63-LEL蛋白表达量高;在咪唑浓度为MCAC-80/100/200/500条件下可洗脱目的蛋白,Western blot检测Ni-NTA agarose纯化蛋白大小位于26 k U和35 k U处。结论在大肠埃希菌中获得了p ET-29a-CD63-LEL蛋白的大量表达,经镍柱亲和层析可得到较纯的p ET-29aCD63-LEL蛋白。
文摘With user-generated content, anyone can De a content creator. This phenomenon has infinitely increased the amount of information circulated online, and it is beeoming harder to efficiently obtain required information. In this paper, we describe how natural language processing and text mining can be parallelized using Hadoop and Message Passing Interface. We propose a parallel web text mining platform that processes massive amounts data quickly and efficiently. Our web knowledge service platform is designed to collect information about the IT and telecommunications industries from the web and process this in-formation using natural language processing and data-mining techniques.
