國立中興大學教學大綱
課程名稱 (中) 生物資訊於植物病理應用實務(6835)
(Eng.) Bioinformatic Applications in Plant Pathology
開課單位 植保碩士學程
課程類別 選修 學分 2 授課教師 張道禾
選課單位 植保碩士學程 / 碩士班 授課使用語言 英文 英文/EMI Y 開課學期 1141
課程簡述 Current biology studies have entered into the omic era. The mass amount of sequencing and high throughput results have raised the attention for programming data analysis. This course aims at the topic of bioinformatic processes related to plant pathology. The case studies with bioinformatics will help students to practice and understand how to use the computational tools to design the experiments and analyse the results.
先修課程名稱
課程含自主學習 Y
課程與核心能力關聯配比(%) 課程目標之教學方法與評量方法
課程目標 核心能力 配比(%) 教學方法 評量方法
1. Introduction of the concepts of bioinformatics
2. Understanding the program we use in class (Online resource and R program)
3. Cases studies in bioinformatics
專題探討/製作
習作
出席狀況
作業
授課內容(單元名稱與內容、習作/每週授課、考試進度-共16週加自主學習)
週次 授課內容
第1週 Introduction and course brief
第2週 R program: Introduction and basic function
第3週 R program: Data analysis and graphics
第4週 Web tools: Galaxy bioinformatic
第5週 Transcriptome analysis: RNAseq raw data, cleaning, and transcriptome assemble
第6週 Transcriptome analysis: differentially expressed genes (DEGs)
第7週 Transcriptome analysis: weighted gene correlation network analysis
第8週 Transcriptome analysis: GO and KEGG pathway analysis
第9週 Midterm
第10週 Image analysis: ImageJ introduction, counting colonies
第11週 Image analysis: Disease symptom analysis, machine learning concept
第12週 Web tools: NCBI, ENSEMBL, TAIR
第13週 Web tools: PlantGDB, Phytozome
第14週 Web tools: benchling
第15週 Genome analysis: Genome annotation and genome comparisons
第16週 Web tools: Protein data bank Protein visulisation: PyMOL Final remarks
自主學習
內容

學習評量方式
Group discussion participation (30%)
Presentation (20%)
Assignment of practices (50%)
教科書&參考書目(書名、作者、書局、代理商、說明)
Khan, A., Singh, S., and Singh, V. K. (2021). “Bioinformatics in Plant Pathology,” in Emerging Trends in Plant Pathology, eds. K. P. Singh, S. Jahagirdar, and B. K. Sarma (Singapore: Springer), 725–844. doi: 10.1007/978-981-15-6275-4_32.
Kabacoff, R.I. (2015). R in action: data analysis and graphics 2nd Ed. (USA: Manning publication).
課程教材(教師個人網址請列在本校內之網址)
1. A comprehensive flowchart showing the step-by-step process from raw sequencing data to analysed results helps students visualise the entire bioinformatics workflow.
2. A pre-loaded virtual machine image with all required bioinformatics tools and sample datasets allows students to start practising immediately without software installation issues.
3. A collection of real plant pathology case studies with accompanying datasets gives students hands-on experience with research problems and their solutions.
4. An interactive command-line cheat sheet listing essential bioinformatics commands and their usage, serving as a quick reference during practical sessions.
課程輔導時間
Friday from 13:00 to 15:00
聯合國全球永續發展目標(連結網址)
04.教育品質   09.工業、創新基礎建設提供體驗課程:N
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更新日期 西元年/月/日:無 列印日期 西元年/月/日:2025 / 8 / 01
MyTB教科書訂購平台:http://www.mytb.com.tw/