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一次學會 Google Office 必備工具：文件 X 試算表 X 簡報 X 雲端硬碟

為了解決Google 試算表篩選 公式的問題，作者吳燦銘 這樣論述：

快速了解Google創新服務與工具 免費擁有Google雲端版的Office軟體 將文件、試算表和簡報安全地儲存在線上 與他人共同編輯文件、試算表或簡報 掌握Google雲端硬碟亮點、管理與使用 　　Google提供雲端版的Office軟體，可以讓使用者以免費的方式，透過瀏覽器將文件、試算表和簡報安全地儲存在線上，並從任何地方進行編輯，還可以邀請他人檢視並共同編輯內容。本書架構相當完整，為了提高閱讀性，各項重點知識會以實作為主、功能說明為輔。各單元精彩內容如下： 　　Google文件 　　˙語音輸入           ˙插入標點符號、特殊字元與方程式 　　˙文字與段落格式設定    

  ˙顯示文件大綱 　　˙離線編輯           ˙變更頁面尺寸 　　˙查看全螢幕文件        ˙在會議中分享畫面與共用文件 　　˙以電子郵件傳送文件      ˙從本機與雲端硬碟插入圖片 　　˙使用網路圖片         ˙圖案的插入與編修 　　˙文字藝術師          ˙頁面設定 　　˙插入表格、增減欄列、合併儲存格˙平均分配列高欄寬 　　˙表格框線與儲存格背景色    ˙文件轉PDF格式 　　˙分享雲端檔案         ˙合併列印外掛程式 　　˙設定合併列印資料來源     ˙選擇合併列印標籤版面 　　˙插入合併欄位         ˙標籤外框編修與調整 　　G

oogle試算表 　　˙儲存格參照與範圍選取     ˙試算表編輯(複製、剪下與貼上) 　　˙欄寛與列高          ˙儲存格格式化 　　˙圖片插入儲存格        ˙自動儲存 　　˙公式與函數應用        ˙多欄位排序 　　˙清單檢視的排序方式      ˙資料篩選 　　˙插入圖表、編輯圖表、圖表編輯器˙資料透視表建立與編輯 　　˙資料透視表欄位配置      ˙資料欄位的展開與摺疊 　　˙資料透視表欄列資料排序與篩選 ˙資料透視表欄列資料的變更 　　˙建立群組與取消群組      ˙資料透視表樣式套用 　　Google簡報 　　˙管理與新增Google簡報     ˙簡報

上傳與下載 　　˙使用語音輸入演講者備忘稿   ˙播放簡報 　　˙在會議中分享簡報畫面     ˙簡報共用與停止共用 　　˙開啟雷射筆進行講解      ˙以「簡報者檢視」模式進行教學 　　˙自動循環播放         ˙為簡報建立副本 　　˙套用／變更主題範本      ˙變更版面配置 　　˙變更文字格式與插入文字藝術師 ˙匯入PowerPoint投影片 　　˙設定轉場切換         ˙加入物件動畫效果 　　˙調整動畫先後順序       ˙插入影片與音訊 　　˙流程圖的插入與美化      ˙表格插入與美化 　　˙圖表插入與編修        ˙圖案繪製與調整 　　Google雲

端硬碟 　　˙共用檔案協同合作編輯     ˙連結雲端硬碟應用程式(App) 　　˙利用表單進行問卷調查     ˙整合Gmail郵件服務 　　˙查看雲端硬碟使用量      ˙上傳檔案／資料夾 　　˙用顏色區隔重要資料夾     ˙下載檔案至電腦 　　˙刪除／救回誤刪檔案      ˙分享與共用雲端資料 　　˙內建文件翻譯功能       ˙辨識聲音轉成文字 　　˙增加Google雲端硬碟容量    ˙合併多個PDF檔 　　˙設定只有你本人可以共用檔案  ˙將雲端硬碟檔案分享給指定的人

Google 試算表篩選 公式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Google 試算表篩選 公式的問題，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.