# |
Date |
Topics |
Slides |
Matlab |
Homework |
Exams |
1 |
Aug 26 |
Why probability and statistics in comutational bioengineering? | Lecture 1 | |||
2 |
Aug 28 |
Random experiments. Sample space, Events, Venn diagramms. Definitions of probability: |
Lecture 2 | |||
3 |
Sep 2 |
Definitions of probability: Paradoxes of inductive definition of probability Combinatorics |
Lecture 3 | |||
4 |
Sep 4 |
Combinatorics (continued) Conditional probability Circuit diagrams Bayes' theorem Specificity/Sensitivity of tests |
Lecture 4 | circuit_template.m | ||
5 |
Sep 9 |
Secretary problem Simpson's paradox Monty Hall problem |
Lecture 5 | monty_hall_template.m | ||
6 |
Sep 11 |
Discrete random varibales, Uniform distribution |
Lecture 6 | uniform_discrete_template.m | hw1.pdf |
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7 |
Sep 16 |
Bernoulli trials Binomial Distribution Poisson Distribution |
Lecture 7 | |||
8 |
Sep 18 |
Poisson distribution in genome assembly | Lecture 8 | poisson_template.m | ||
9 |
Sep 23 |
Geometric distribution. Mitochondrial Eve & |
Lecture 9 |
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10 |
Sep 25 |
Negative Binomial Distribution Cancer: Driver and Passenger genes |
Lecture 10 | hw1_with_solutions.pdf | ||
11 |
Sep 30 |
Probability Density Function, CDF, CCDF, Mean, Variance, Std Uniform continuous distribution. Constant rate (Poisson) process. Exponential distribution. |
Lecture 11 | hw2.pdf | ||
12 |
Oct 2 |
Erlang and Gamma distributions Gaussian distribution Standardizing and working with the CDF table |
Lecture 12 | |||
13 |
Oct 7 |
Fitting Gaussian distribution to the data for binding energies of protein-protein interactions Multiple random variables. Joint, Marginal, and Conditional PMFs Statistical independence of random variables |
Lecture 13 | hw2_with_solutions.pdf | ||
14 |
Oct 9 |
Covariance Correlation coefficients: |
Lecture 14 | |||
15 |
Oct 14 |
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16 |
Oct 16 |
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17 |
Oct 21 |
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18 |
Oct 23 |
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19 |
Oct 28 |
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20 | Oct 30
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21 |
Nov 4 |
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22 |
Nov 6 |
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23 |
Nov 11 |
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24 |
Nov 13 |
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25 |
Nov 18 |
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26 |
Nov 20 |
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27 |
Dec 2 |
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28 | Dec 4 | |||||
29 | Dec 9 | |||||
FINAL EXAM |