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Date

Topics

Slides

Matlab

Homework
(not graded)

Exams
1

Aug 24

 Why probability and statistics in comutational bioengineering? Lecture_1.pdf      
2

Aug 26

Random experiments. Sample space, Events, Venn diagramms. 

Definitions of probability:
Statistical (part 1)

 Lecture2.pdf      
3

Aug 31

Definitions of probability:
Statistical (continued)

Definitions of probability:
Inductive. 

Paradoxes of inductive definition of probability

Combinatorics

 Lecture3.pdf

coin_toss_template.m

coin_toss.m

    
4

Sep 2

Combinatorics (continued)

Probability axioms

Conditional probability

Independence of events

Circuit diagrams

 Lecture4.pdf      
5

Sep 7

Circuit diagrams (continued)

Bayes' theorem

Specificity/Sensitivity of tests

 Lecture5.pdf

circuit_template.m

circuit.m

    
6

Sep 9 

Bayes' theorem (continued)

Monty Hall problem

 Lecture6.pdf

monty_hall_template.m

monty_hall.m

 hw1.pdf


 
7

Sep 14

Discrete random varibales,

PMF. CDF, CCDF, 
Mean, Variance, Skewness

Uniform distribution

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

 Lecture7.pdf

 

    
8

Sep 16

Bernoulli trials

Binomial Distribution

Secretary Problem

 Lecture8.pdf

binomial_template.m

binomial.m

 hw1_with_solutions.pdf  
9

Sep 21

Binomial Distribution (continued)

Poisson Distribution

Genome Assembly

 Lecture9.pdf

poisson_template.m

poisson.m

    
10

Sep 23

Geometric distribution.

Phylogenetic trees and time to the most recent common ancestor. 

Mitochondrial Eve, Y-chromosome Adam and ancestry of nuclear DNA

 Lecture10.pdf

 

    
11

Sep 28

Mitochondrial Eveen (continued)

Negative Binomial Distribution

Cancer: Driver and Passanger genes/mutations

 Lecture11.pdf

geometric_negative_binomial_template.m

geometric_negative_binomial.m

    
12

Sep 30

Continuous random variables.

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

Uniform continuous distribution. 

Constant rate (Poisson) process.

Exponential distribution.

 Lecture12.pdf

 

    
13

Oct 5

 Erland, Gamma, Gaussian distributions Lecture13.pdf

exponential_gamma_template.m

exponential_gamma.m

    
14

Oct 7 

Gaussian (continued)

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

 Lecture14.pdf PINT_binding_energy.mat hw2.pdf  
15

Oct 12

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

Statistical independence of variables

 Lecture15.pdf      
16

Oct 14

Covariance

Correlation coefficients:
Pearson, Spearman

 Lecture16.pdf

Excercise #1:
correlation_template.m
correlation.m

Exercise #2:
cancer_wdbc.mat
cancer_wdbc_cc_analysis_template.m
cancer_wdbc_cc_analysis.m

 hw2_with_solutions.pdf  
17

Oct 19

 Midterm preparation Lecture17.pdf       
 

Oct 21

 Midterm        
18

Oct 26

 Samples, histograms, 
median, quartiles, percentiles
Box-and-whisker plots		 Lecture18.pdf

quartiles_template.m

quartiles.m

 

    
19

Oct 28

Sample mean. Its mean and variance (standard error). Central limit theorem.

Parameter point estimation (part one)..

 Lecture19.pdf

central_limit_theorem_template.m

central_limit_theorem.m

 hw3.pdf  
20

Nov 2

 Parameter point estimation. Method of moments and Maximum Likelihood Estimator Lecture20.pdf

moment_estimators_template.m

moment_estimators.m

    
21

Nov 4

 Sample variance; Confidence intervals of population mean and variance; Student-t and chi-squared distributions Lecture21.pdf

confidence_intervals_template.m

confidence_intervals.m

 

 hw3_with_answers.pdf  
22

Nov 9

 Confidence intervals (continued). Hypothesis testing Lecture22.pdf

dark_vs_milk_chocolate_analysis_template.m

dark_vs_milk_chocolate_analysis.m

 hw4.pdf  
23

Nov 11

 Pearson's chi-square Goodness of Fit (GOF) test Lecture23.pdf

m_and_m_analysis_template.m

m_and_m_analysis.m

    
24

Nov 16

 Linear regression: two variables   Lecture24.pdf

regression_multiple_template.m

expression_table.mat

 hw4_with_answers.pdf  
25

Nov 18

 Multiple Linear Regression.
PCA (part one)		 Lecture25.pdf

 

 hw5.pdf  
26

Nov 30

PCA (part two)

Clustering 

 Lecture26.pdf

cancer_wdbc_pca_analysis.m

clustering.m

    
27

Dec 2

Important nodes in networks: degree, PageRank,  betweenness-centraility.

Co-expression and disease-disease networks analyzed using Gephi software

 Lecture27.pdf

gephi_network_analysis_exercise.docx

gephi_install_notes.docx

coexpression_network_random start.gephi

disease_disease_random_start.gephi

 hw5_with_answers.pdf  
28 Dec 7 Final exam preparation Lecture28.pdf      

FINAL EXAM

Dec 10 

7pm-10pm

 305 Materials Science & Eng Bld

(the same room as classes)