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生物信息學：導論與方法培訓

Introduction and History of Bioinformatics

Welcome to “Bioinformatics: Introduction and Methods! Upon completion of this module

you will be able to: become familiar with the essential concepts of bioinformatics; explore

the history of this young area; experience how rapidly bioinformatics is growing.

Our supplementary materials will give you a better understanding of the course lectures through they are not required in quizzes or exams

Sequence Alignment

Upon completion of this module,

you will be able to: describe dynamic programming based sequence alignment algorithms;

differentiate between the Needleman-Wunsch algorithm for global alignment and

the Smith-Waterman algorithm for local alignment; examine the principles behind gap penalty

and time complexity calculation which is crucial for you to apply current bioinformatic tools

in your research; experience the discovery of Smith-Waterman algorithm with Dr. Michael Waterman himself.

Sequence Database Search

Upon completion of this module, you will be able to: become familiar with sequence databse search

and most common databases; explore the algoritm behind

BLAST and the evaluation of BLAST results; ajdust BLAST parameters base on your own research project.

Markov Model

Upon completion of this module, you will be able to: recognize state transitions,

Markov chain and Markov models; create a hidden Markov model by yourself;

make predictuions in a real biological problem with hidden Markov model.

Markov Model

Upon completion of this module, you will be able to: recognize state transitions,

Markov chain and Markov models; create a hidden Markov model by yourself;

make predictuions in a real biological problem with hidden Markov model.

Functional Prediction of Genetic Variants

Upon completion of this module you will able to: describe what is variant prediction and how to carry

out variant predictions; associate variant databases with your own research projects after you get a list of variants;

recognize different principles behind prediction tools and know how to use tools such as SIFT,

Polyphen and SAPRED according to your won scientific problem.

Mid-term Exam

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Next Generation Seq

uencing: Transcriptome Analysis, and RNA-SeqUpon completion of this module,

you will be able to: describe how transcriptome data were generated; master the algorithm used

in transcriptome analysis; explore how the RNA-seq data were analyzed. This module is required before entering Module 9.

Prediction and Analysis of Noncoding RNA

Upon completion of this module, you will be able to: Analyze non-coding RNAs from transcriptome data;

identify long noncoding RNA (lncRNA) from NGS data and predict their functions.

Ontology and Identification of Molecular Pathways

Upon completion of this module, you will be able to: define ontology and gene ontology,

explore KEGG pathway databses; examine annotations in Gene Ontology;

identify pathways with KOBAS and apply the pipeline to drug addition study.

Bioinformatics Database and Software Resources

Upon completion of this module, you will be able to describe

the most important bioinformatic resources including databases

and software tools; explore both centralized resources such as NCBI, EBI,

UCSC genome browser and lots of individual resources; associate

all your bioinformatic problems with certain resources to refer to.

Origination of New Genes

Upon completion of this case study module,

you will be able to: experience how to apply bioinformatic data,

methods and analyses to study an important problem in evolutionary biology;

examine how to detect and study the origination, evolution and function of species-specific new genes;

create phylogenetic trees with your own data (not required) with Dr. Manyuan Long,

a world-renowned pioneer and expert on new genes from University of Chicago.

Evolution function analysis of DNA methyltransferase

Upon completion of this case study module, you will be able to:

experience how to use bioinformatic methods to study the function and evolution of DNA methylases;

share with Dr. Gang Pei, president of Tongji University and member of the Chinese Academy of Science,

the experiences in scientific research and thought about MOOC.

Final Exam

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