This course is an introduction to the theoretical tools that are used to understand the emerging behavior of complex biological networks. Systems Biology is a systemic approach to understand the biological phenomena that occurs inside a cell at the molecular level.

## Slides used in classes

Most classes are done on a whiteboard, so you need to keep your own paper copy. Some of these classes are later transcribed into webpage and published here. When the class used slides, they are published here.

## Example Jupyter code

- Pascal’s Triangle. [Web page]
- Probabilities in R. [Web page]
- Law of Large Numbers. [Web page]
- Testing the hypothesis of finger randomness. [Web page]
- Testing again with a different score function. [Web page]
- Testing two samples. Doing the same test many times. [Web page]

## Online material

- The lady tasting tea: Using experimental methods to introduce inference statistics. (PDF).
- A lady tasting tea and other applications of Categorical Data Analysis. (PDF).
- You Can Load a Die, But You Cant Bias a Coin. (ResearchGate page).
- A Class Project in Survey Sampling. (ResearchGate page).
- Debunking the P-value with Statistics. (Backyard Brains website).
- The p value and the base rate fallacy. (Statistics Done Wrong website).
- Paired Sample T-Test. (Statistics Solutions website).
- Comparing Two Population Means: Paired Data. (Pennsylvania State University).
- Hypothesis Test: Difference Between Paired Means. (web page)
- RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR (Bioconductor tutorial).

## Contact

The forum of the course is at https://groups.google.com/d/forum/iu-systems-biology. You can also participate writing an email to iu-systems-biology@googlegroups.com. Feel free to use it to ask any question or give any answer.

- From
*genotype*to*phenotype* - Behavior emerging from networks
- Metabolic
- Signaling
- Regulatory
- Transcriptional
- Post-transcriptional

### Transcriptional Regulation

- Which genes code for
*transcription factors*? - Which are their
*binding sites*? - How do they change gene expression?
- enhancer
- repressor

### Binding Sites

- Few experimental results. Expensive
- How can we generalize them?
- Probability theory
- other approaches