Intro2CompBio

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An undergraduate class on introduction to computational biology by Professor Shao Li.

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### Introduction To Computational Biology
_This is an advanced undergraduate class about introduction to computational biology by Professor Shao Li. Students should know the junior probability and statistics, linear algebra, and basic calculas before choosing this class. The basic capacity for programming is required._  
TA: Songpeng Zu and Peng Zhang  
Created Time: 2015-08-24

In this year, we try a new style for the exercise classes (5 times * 90 min in one semester, while the class in total involves 16 times * 90 mins in one semester). 
- We partition the students into three groups, and each group focuses on one research direction on Bioinformatics (such as GWAS, sequence data analysis methods, network medicine, and so on). 
- In every exercise class, each group should give a presentation on one specific ariticle based on the given research direction (not reviews or other types). 
- Then the TA would give a short introduction, less than 30 mins, on the basic statistical methods or algorithms that are important for biological data analysis, such as principle component analysis (*PCA*), clustering, generalised linear regression and so on.

Reading papers, and making the presentatons are quite useful for the students, also the basic algorighms or statistical methods. Since the time in class is limited, we only show the important concepts, and let them study and finish the homework by themselves. BTW, Github is a good way to submit and view the codes both for the students and TAs.

In this semester, we covered the useage of R (especially Rcpp, Rmd, ggplot), the basic concepts on statistics (such as maximum likelihood principle, Bayesian formula,  p-value and multiple testing, linear regression), the basic tools on machine learning (logistic regression, PCA, clustering), and the lagrange tool on the optimization. 
  
We find that we need a unified material for their references. So we plan to summarise our exercise class and write a _textbook_ specific for this task.

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