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Date

Topics

Slides

Matlab

Homework

Exams

1

Jan 21

Why probability and statistics in comutational bioengineering?Lecture 1   
2

Jan 23

Random experiments. Sample space, Events, Venn diagramms. 

Definitions of probability:
Statistical (part 1)

Lecture 2   
3

Jan 28

Definitions of probability:
Statistical (continued)

Definitions of probability:
Inductive. 

Paradoxes of inductive definition of probability

Lecture 3coin_toss_template.m  
4

Jan 30

Combinatorics 

Probability axioms

Conditional probability

Lecture 4   
5

Feb 4

Independence of events

Circuit diagrams 

Bayes' theorem

Specificity/Sensitivity of tests

Lecture 5   
6

Feb 6

Secretary problem

Simpson's paradox

Monty Hall problem

Lecture 6monty_hall_template.m 


 

7

Feb 11

Discrete random varibales,

PMF. CDF, CCDF, 
Mean, Variance, Skewness

Uniform distribution

The distribution of the
Ct value in COVID-19
PCR tests (part 1(

Lecture 7

 

  
8

Feb 13

Bernoulli trial

Binomial distribution

Lecture 8

binomial_template.m

binomial.m

  
Online

Feb 18

Poisson distribution.Online lecture

Online_lecture_video

 

  
9

Feb 20

 

Applications of the Poisson distribution.

Genome Assembly.

de Bruijn graphs.


 Lecture 9

 

  
10

Feb 25

 

Geometric distribution.

Phylogenetic trees and time to the most recent common ancestor. 

Mitochondrial Eve, Y-chromosome Adam.

 Lecture 10

 geometric_and_negative_binomial_template.m

  
11

Feb 27

 

Mitochondrial Eve 
Y-chromosome Adam 
and nuclear DNA ancestors  (continued)

Negative Binomial Distribution

Cancer: Driver and Passenger genes/mutations

 Lecture 11

 

  
12

Mar 4

 

Continuous random variables.

Probability Density Function, CDF, CCDF, Mean, Variance, Std

Uniform continuous distribution. 

Constant rate (Poisson) process.

 Lecture 12   
13

Mar 6

Exponential, Erland, and Gamma distributions. Gaussian distribution.
Normalization. Z-scores
 Lecture 13   
14

Mar 11

 Class in session Midterm review.

Midterm exam at CBTF 
March 11- March 13		Lecture 14
   
Midterm

Mar 13

 No class due to the Midterm exam    
15

Mar 25

Fitting Gaussian distribution to the data on binding energies of protein-protein interactions.

Multiple random variables. Joint, Marginal, and Conditional PMFs or PDFs.

Statistical independence of variables.


 Lecture 15  Data:
PINT_binding_energy.mat

  Analysis instructions:

PINT_binding_energy.m




  
16

Mar 27

 

Covariance

Correlation coefficients:
Pearson, Spearman

 Lecture 16 

correlation_template.m

cancer_wdbc_cc_analysis_template.m

cancer_wdbc.mat

  
17

Apr 1

   boxplot_template.m

https://onlinestatbook.com/stat_sim/sampling_dist/
 
18

Apr 3

     
19

Apr 8

     
20

Apr 10

     
21

Apr 15

     
22

Apr 17

  

 

  
23

Apr 22

  

 

  
24

Apr 24

  

 

  
25

Apr 29

  

 

  
26

May 1

     
27May 6     

FINAL EXAM