教學大綱 Syllabus

科目名稱：生物資訊概論與實務

Course Name: Theory and Practice of Bioinformatics

學年學期：113-1 Fall Semester, 2024
科目代碼：753845001 Course No.753845001

修別：選

Type of Credit: Elective

3.0

學分數

Credit(s)

預收人數

Number of Students

課程資料Course Details

開課單位：資碩工一、資碩計一 Course Department:Computer Science/M/1
授課老師：張家銘 Instructor: CHANG JIA-MING
先修科目：無Prerequisite(N/A)
上課時間：四234 Session: thu09-12

課程簡介Course Description

Bioinformatics is an interdisciplinary and emerging field, which develops methods and software tools for understanding biological data. Being a Bioinformatician requires an integrated skill set, including computer science, statistics, mathematics, and engineering. This course will introduce students to this rapidly growing topic and equip them with some of its fundamental principles, related algorithms, and programming skill as well as useful tools.

核心能力分析圖 Core Competence Analysis Chart

能力項目說明

課程目標與學習成效Course Objectives & Learning Outcomes

生物資訊學是一門結合生物學、計算機科學及資訊科技的新研究領域。本課將透過個案舉例形式，來介紹蛋白質體學、基因體學和比較生物資訊學中資訊技術原理與應用；除了課堂講授，亦透過實務操作，利用網路資源或撰寫小程式，來完成生物資訊的分析，期末作業以團隊模式來進行，進而訓練學生合作能力，此為就業重要經驗。修讀本課程後，非生科背景的學生將具備基礎生物資料科學分析能力，包括：演算法設計、應用機器學習與測試統計方法，未來可以嘗試生資產業相關工作。

This course is dedicated to proteomics, genomics and comparative bioinformatics by case study. Final project is based on teamwork form which is an essential skill in the field of Bioinformatics. After the course, students should have ability to conduct bioinformatic data science analysis include designing algorithm, applying machine learning and performing statistical test. They can be qualified for jobs in the field of biotechnology industry.

每周課程進度與作業要求 Course Schedule & Requirements

教學週次Course Week	彈性補充教學週次Flexible Supplemental Instruction Week	彈性補充教學類別Flexible Supplemental Instruction Type
17+1週17+1 weeks	第 18 週 Week 18	課程相關線上學習Course-related online learning

周次	課程主題	課程內容與指定閱讀	教學活動與作業	學習投入時數
1	Introduction	What is bioinformatics? The central dogma of molecular biology: DNA, mRNA, protein	The DNA Journey 天下文化觀念生物學1~4 Canadian Bioinformatics Workshops (all slides and video are available)	6
2	Sequence alignment	Why do we need sequence alignment? Its application in structure homology and evolutionary modeling context Dynamic programming	SEAVIEW : Sequence alignment editor T-Coffee documentation	6
3	Pairwise Sequence alignment	Global & Local alignments Linear space algorithm BLAST	NCBI BLAST server BLAST by O'Reilly Media	6
4	Multiple Sequence alignment	The variation of the algorithms, which one is better? Another issue: huge amount of data	T-Coffee web server PSI/TM-Coffee web server PSI/TM-Coffee: Floden, E. W. et al. PSI/TM-Coffee: a web server for fast and accurate multiple sequence alignments of regular and transmembrane proteins using homology extension on reduced databases. Nucleic Acids Res. 44, W339–43 (2016). PSI-Coffee: Chang, J.-M. M., Di Tommaso, P., Taly, J.-F. F. & Notredame, C. Accurate multiple sequence alignment of transmembrane proteins with PSI-Coffee. BMC Bioinformatics 13 Suppl 4, S1 (2012).	6
5	Double Ten National Day Holiday
6	Sequence alignment post-process	Uncertainty and its effect on downstream analysis How do we detect uncertainty?	TCS web server TCS: Chang, J.-M. M., Di Tommaso, P. & Notredame, C. TCS: a new multiple sequence alignment reliability measure to estimate alignment accuracy and improve phylogenetic tree reconstruction.Mol. Biol. Evol. 31, 1625–37 (2014).	6
7	Midterm	One A4 page	Databases of rRNA sequences and associated software summary by Manolo Gouy The rRNA WWW Server by Antwerp, Belgium The Ribosomal Database Project by Michigan State University	6
8	Phylogenetic tree 1/2	Probabilistic and ideal-data models Character/parsimony-based methods	Programs for molecular phylogeny summary by Manolo Gouy PHYLIP: an extensive package of programs for all platforms PAUP: a very performing commercial package PHYLO_WIN: a graphical interface, for unix only MrBayes: Bayesian phylogenetic analysis PhyML: fast maximum likelihood tree building WWW-interface at Institut Pasteur, Paris	6
9	Phylogenetic tree 2/2	Distance-based methods: UPGMA, NJ Maximum-likelihood methods: PhyML	HYPROSP: Wu, K.-P., Lin, H.-N., Chang, J.-M., Sung, T.-Y. & Hsu, W.-L. HYPROSP: a hybrid protein secondary structure prediction algorithm—a knowledge-based approach. Nucleic Acids Research 32, 5059–5065 (2004). HYPROSPII: Lin, H.-N., Chang, J.-M., Wu, K.-P., Sung, T.-Y. & Hsu, W.-L. HYPROSP II-A knowledge-based hybrid method for protein secondary structure prediction based on local prediction confidence. Bioinformatics 21, 3227–3233 (2005).	6
10	Protein secondary structure prediction	Neural network approach Knowledge-based approach	The Critical Assessment of protein Function Annotation algorithms (CAFA) CAFA1: Radivojac, P. et al. A large-scale evaluation of computational protein function prediction. Nat. Methods 10, 221–7 (2013). CAFA2: Jiang, Y. et al. An expanded evaluation of protein function prediction methods shows an improvement in accuracy. arXiv preprint arXiv:1601.00891 (2016). at	6
11	Protein functional class prediction	Machine learning Feature reduction	PSLDoc: Chang, J.-M. M. et al. PSLDoc: Protein subcellular localization prediction based on gapped-dipeptides and probabilistic latent semantic analysis. Proteins 72, 693–710 (2008) PSLDoc2: Chang, J.-M. M. et al. Efficient and interpretable prediction of protein functional classes by correspondence analysis and compact set relations. PLoS ONE 8, e75542 (2013)
12	Genomics1	What are genes and genomes? How does a gene express and regulate?		3
13	Genomics2	The Human Genome Project Gene finding	The Assemblathon	6
14	Next Generation Sequencing	RNA-Seq: large amounts of data How to identify significant expressions?	Applications of next-generation sequencing by Nature Reviews Genetics	6
15	Comparative genomics 1	Genome alignment Phylogenomics	The Alignathon	6
16	Comparative genomics 2	Single-nucleotide polymorphisms related to diseases	HaploReg: a tool for exploring annotations of the noncoding genome at variants on haplotype blocks ClinVar: aggregates information about genomic variation and its relationship to human health	6
17	Final project presentation	Rubrics/評分量尺
18	Self-organized learning	ENCODE: Encyclopedia of DNA Elements modENCODE: model organism Encyclopedia of DNA Elements NIH Roadmap Epigenomics 1000 Genomes UCSC/Ensembl genome browser WashU epi-genetics browser RCSB Protein Data Bank (PDB) NCBI Sequence Read Archive (SRA)	Collected papers for Epigenome Roadmap Epigenetics by Nature Reviews Genetics ENCODE modENCODE Roadmap Epigenomics project	3

授課方式Teaching Approach

60%

講述 Lecture

15%

討論 Discussion

15%

小組活動 Group activity

10%

數位學習 E-learning

其他： Others:

評量工具與策略、評分標準成效Evaluation Criteria

作業 55%
期中考 15%
期末專題 20%
上課表現 10%

指定/參考書目Textbook & References

主要參考書籍
Introduction to Bioinformatics
Author: Arthur Lesk.
Publisher: Oxford University Press; 4 edition (January 1, 2014)
ISBN: 0199651566

其他參考書籍
Bioinformatics For Dummies
Author: Jean Michel Claverie, Cedric Notredame
Publisher: For Dummies; 2 edition (December 18, 2006)
ISBN: 0470089857

Bioinformatics: Sequence and Genome Analysis
Author: David W. Mount
Publisher: 2nd Edition, Cold Spring Harbor Lab. Press

Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins, 3rd Edition
Author: Andreas D. Baxevanis, B. F. Francis Ouellette, Wuket Kussm

Statistical Methods in Bioinformatics: An Introduction (Statistics for Biology and Health)
Author: Warren J. Ewens and Gregory R. Grant

Introduction to Bioinformatics Algorithms
Author: Jones Neil J. and Pevzner Pavel A.

Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids Paperback
Author: Richard Durbin, Sean R. Eddy, Anders Krogh, Graeme Mitchison

已申請之圖書館指定參考書目圖書館指定參考書查詢 |相關處理要點

課程相關連結Course Related Links

https://bioinfcoursechanglabtw.readthedocs.io/en/latest/

課程附件Course Attachments

課程進行中，使用智慧型手機、平板等隨身設備 To Use Smart Devices During the Class

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