JavaScript 物件轉 字 串的問題，透過圖書和論文來找解法和答案更準確安心。 我們找到下列推薦必買和特價產品懶人包

圖像 Angular 開發入門：打造高靈活度的網頁應用程式(iT邦幫忙鐵人賽系列書)

為了解決JavaScript 物件轉 字 串的問題，作者黃俊壹(阿壹) 這樣論述：

本書內容改編自第 12 屆 iT 邦幫忙鐵人賽 Modern Web 組佳作網路系列文章 《Angular 全集中筆記》 　　Angular 是 Google 所發展出來的完整前端框架，可以用來開發網頁、桌面與行動等各種應用程式；也提供了 Angular CLI 來簡化開發過程中事務型的作業。 　　本書以循序漸進的方式，一層一層地由淺入深的介紹 Angular 前端框架，並搭配著圖像說明與實務案例，讓讀者更容易了解如何利用 Angular 開發高靈活性的應用程式。 　　目標讀者 　　1. 對前端框架有興趣的初學者。 　　2. 想要完整了解 Angular 前端框架的前端工程師。 　　

3. 想轉職前端工程師的大大們。 本書特色 　　從零開始介紹 Angular 的基礎知識、各種類型的元件、依賴注入等核心內容，幫助讀者快速入門。 　　利用圖像化方式說明 Angular 各種觀念，幫助讀者更容易地了解在多種不同程式或元件間的抽象互動。 　　透過變動的需求範例程式，從簡入深的使用 Angular 各種概念，帶領讀者更容易地連結前端技術與使用者需求。 　　完整介紹 Angular CLI 各種命令，讓讀者熟悉在開發過程中，利用 CLI 命令簡化事務型的作業。 專業推薦 　　目前世面上講授 Angular 的中文書籍很少，但這本「圖像 Angular 開發入門」非常適合新手入

門，對於想要進入前端框架領域的新手來說，是個相當不錯的選擇。書中講解不少 Angular 實戰開發中必須瞭解的重要觀念，搭配著完整的範例程式碼，初學者可以直接從線上就能體驗 Angular 的開發過程，也可以透過互動的方式快速掌握精髓之處。 　　多奇數位創意 技術總監、Google Developer Expert、Microsoft MVP 　　———————————————Will 保哥 | 2021/8/16 　　部落格：blog.miniasp.com/ 　　臉書專頁：www.facebook.com/will.fans/  

JavaScript 物件轉 字 串進入發燒排行的影片

An Integrated Approach For Uncovering Novel DNA Methylation Biomarkers For Non-small Cell Lung Carcinoma

為了解決JavaScript 物件轉 字 串的問題，作者VAIBHAV KUMAR SUNKARIA 這樣論述：

Introduction - Lung cancer is one of primal and ubiquitous cause of cancer related fatalities in the world. Leading cause of these fatalities is non-small cell lung cancer (NSCLC) with a proportion of 85%. The major subtypes of NSCLC are Lung Adenocarcinoma (LUAD) and Lung Small Cell Carcinoma (LUS

C). Early-stage surgical detection and removal of tumor offers a favorable prognosis and better survival rates. However, a major portion of 75% subjects have stage III/IV at the time of diagnosis and despite advanced major developments in oncology survival rates remain poor. Carcinogens produce wide

spread DNA methylation changes within cells. These changes are characterized by globally hyper or hypo methylated regions around CpG islands, many of these changes occur early in tumorigenesis and are highly prevalent across a tumor type.Structure - This research work took advantage of publicly avai

lable methylation profiling resources and relevant comorbidities for lung cancer patients extracted from meta-analysis of scientific review and journal available at PubMed and CNKI search which were combined systematically to explore effective DNA methylation markers for NSCLC. We also tried to iden

tify common CpG loci between Caucasian, Black and Asian racial groups for identifying ubiquitous candidate genes thoroughly. Statistical analysis and GO ontology were also conducted to explore associated novel biomarkers. These novel findings could facilitate design of accurate diagnostic panel for

practical clinical relevance.Methodology - DNA methylation profiles were extracted from TCGA for 418 LUAD and 370 LUSC tissue samples from patients compared with 32 and 42 non-malignant ones respectively. Standard pipeline was conducted to discover significant differentially methylated sites as prim

ary biomarkers. Secondary biomarkers were extracted by incorporating genes associated with comorbidities from meta-analysis of research articles. Concordant candidates were utilized for NSCLC relevant biomarker candidates. Gene ontology annotations were used to calculate gene-pair distance matrix fo

r all candidate biomarkers. Clustering algorithms were utilized to categorize candidate genes into different functional groups using the gene distance matrix. There were 35 CpG loci identified by comparing TCGA training cohort with GEO testing cohort from these functional groups, and 4 gene-based pa

nel was devised after finding highly discriminatory diagnostic panel through combinatorial validation of each functional cluster.Results – To evaluate the gene panel for NSCLC, the methylation levels of SCT(Secritin), FOXD3(Forkhead Box D3), TRIM58(Tripartite Motif Containing 58) and TAC1(Tachikinin

1) were tested. Individually each gene showed significant methylation difference between LUAD and LUSC training cohort. Combined 4-gene panel AUC, sensitivity/specificity were evaluated with 0.9596, 90.43%/100% in LUAD; 0.949, 86.95%/98.21% in LUSC TCGA training cohort; 0.94, 85.92%/97.37 in GEO 66

836; 0.91,89.17%/100% in GEO 83842 smokers; 0.948, 91.67%/100% in GEO83842 non-smokers independent testing cohort. Our study validates SCT, FOXD3, TRIM58 and TAC1 based gene panel has great potential in early recognition of NSCLC undetermined lung nodules. The findings can yield universally accurate

and robust markers facilitating early diagnosis and rapid severity examination.