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翻倍效率工作術：不會就太可惜的Excel必學函數(第三版) (大數據時代必備的資料統計整理與運算力)

為了解決Excel 合併 列 印 多筆的問題，作者文淵閣工作室 這樣論述：

　　近3萬名讀者見證的Excel函數暢銷經典！  　　最新升級增強進化版！127個省時有效率的超實用範例！  　　給你大數據時代必備的資料統計整理與運算力！    　　《超值加贈》  　　Excel快速鍵速查表/函數速查表/函數索引表/全書範例檔  　　理財分析計算教學PDF/消費數據統計影音教學    　　【人力資源】【行政秘書】【財務會計】【決策分析】【大數據處理】必學函數  　　依用途、函數名稱有效整理歸類，隨時查找最快速！    　　◎ 127個範例隨查即用超效率  　　嚴選使用度最高，涵蓋生活、職場上最實用的函數與實例。沒有Excel版本之分，隨時替換套用最便利。搭配函數詳細解說

+依字母排序速查索引表，想提昇工作效率就要懂得靈活運用工具！    　　◎ 一分鐘搞定大量數據資料沒問題  　　老闆交辦工作不能等，但資料缺失、混亂、重複怎麼辦？不會程式也能秒用Excel整理大量數據，利用函數輕鬆處理資料，快速解決眼前一堆複雑惱人的報表。    　　【人力資源】  　　計算年資與特別休假日天數  　　計算加班費  　　計算新進員工試用期滿的日期  　　顯示日期應對的星期值  　　計算不含國定假日的實際工作天數  　　計算上班工時與薪資  　　統計符合條件的員工人數  　　統計人員分佈的中位值與眾數  　　業績達整體績效70%以上的評比“優”  　　..............

.more  　 　　【財務會計】  　　各部門員工薪資小計與總計  　　計算每個月累計薪資  　　加總多個工作表內的銷售金額  　　同時計算多個數值相乘的值  　　加總符合單一或多個條件的數值  　　取出符合條件的資料並加總  　　計算退休金每期應付金額  　　計算基金投資的報酬率  　　...............more  　　 　　【行政秘書】  　　只計算篩選出來的資料  　　依指定條件進行金額計算  　　星期六、日分別以綠、紅文字標示  　　國定假日用淺橘色文字標示  　　以提醒文字取代函數的錯誤訊息  　　限定只能輸入半型字元  　　限定不能輸入重複的資料  　　用色彩標示每隔

一列的資料項目底色  　　由課程表取得各課程費用  　　...............more  　　 　　【決策分析】  　　求預算內可購買的商品數量與餘額  　　從商品存貨數量管理庫存  　　從商品入庫日期取得各月份入庫數量  　　從商品入庫日期取得各季入庫數量  　　查詢特定商品的進貨日期、金額與總額  　　分析公司雜項支出最多的項目  　　計算最高與最低績效值  　　統計年度支出的前二名金額與品名  　　查詢最高進貨額的進貨日期  　　...............more  　　 　　【大數據處理】  　　將缺失資料自動填滿  　　刪除空白、()和換行符號  　　檢查數值資料中是否摻

雜了文字  　　限定只能輸入半形字元  　　限定輸入的訂單數量不能少於100份  　　限定統一編號輸入的格式與字數  　　限定不能輸入未來的日期  　　限定不能於休息日輸入預訂資料  　　限定名冊中員工編號不能重複輸入  　　下拉式選單填入重複性的資料  　　將單欄資料轉成多欄  　　合併多個工作表資料  　　...............more  　 　　等更多精選實用函數　　

Excel 合併 列 印 多筆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Excel 合併 列 印 多筆的問題，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.