Homework

All quizzes and homework should be sent to (andres.aravena+cmb@istanbul.edu.tr) before the deadline to get a grade. Please be careful, otherwise you will get a grade zero.

• Homework 1 (Deadline: Monday 2 of November)

• Homework 2 (Deadline: Monday 16 of November at 11:00).
  Practice for midterm exam. Vectors, indices, and general ideas about using R.

• Homework 3 (Deadline: Monday 23 of November at 11:00).
  Practice for midterm exam. Vectors and indices, again.

• Homework 4 (Deadline: Monday 30 of November at 11:00).
  Practice for midterm exam. Tidying up real-life data.

• Homework 5 (Deadline: Monday 11 of January at 11:00).
  Practice for final exam. Plots and linear models.

Classes

Here you will find the slides from the classes and other supplementary material. Notice that some things are said but not written, so you better take good notes. We recommend taking notes with pen and paper using the Cornell Method.

• Class 1: Why “Computing in Molecular Biology”?. (Oct 19, 2020). [Video],[Slides].
  What is a computer? Why do we care?
• Class 2: What is a computer?. (Oct 19, 2020). [Video],[Slides].
  What is a computer? How do they represent information?What are its parts and how do they interact?
• Class 3: Folders and Files. (Oct 19, 2020). [Video],[Slides].
  What is a computer? What are its parts and how do they interact?
• Class 4: Structured Documents. (Oct 26, 2020). [Video],[Slides].
  Introduction to Rstudio and to Markdown.
• Class 5: Structured text files with Markdown. (Oct 26, 2020). [Video],[Slides].
  Structured text files.
• Class 6: Using R and RStudio. (Oct 26, 2020). [Video],[Slides].
  Basic usage of RStudio. Introduction to R.
• Class 7: Learning R Language. (Nov 2, 2020). [Video],[Slides].
  Introduction to R Language.
• Class 8: Vectors. (Nov 2, 2020). [Video],[Slides].
  Handling several values in a single variable.
• Class 9: More about Rmarkdown. (Nov 2, 2020). [Video],[Slides].
  Headers, metadata, YAML, bibliographic references, footnotes, equations. How to share error messages and ask for help. Other systems of structured text: HTML, LaTeX.
• Class 10: Logic and Text vectors. (Nov 9, 2020). [Video],[Slides].
  Things that are not numbers.
• Class 11: Indices. (Nov 9, 2020). [Video],[Slides].
  Use a vector to look inside another vector and change it.
• Class 12: Practice with vectors in R. (Nov 9, 2020). [Video],[Slides].
  Using COVID data.
• Class 13: Tibbles and data frames. (Nov 16, 2020). [Video],[Slides].
  Reading data from the real world. New way of doing data frames. Combining filters.
• Class 14: Digital Signatures. (Nov 16, 2020). [Video],[Slides].
  Do I have your homework?
• Class 15: Practice with Tibbles. (Nov 16, 2020). [Video],[Slides].
  Practice makes perfect
• Class 16: Telling stories. (Nov 23, 2019). [Video],[Slides].
  Telling stories about data. Many averages, quartiles, quantiles, percentiles, summary. Introduction to Descriptive Statistics.
• Class 18: Practice on tidying up data. (Nov 23, 2020). [Video],[Slides].
  A protocol to get useful data from bad data.
• Class 19: Practice, practice, practice. (Nov 30, 2020). [Video],[Slides].
  Get ready for midterm exam.
• Class 20: Factors. (Dec 21, 2020). [Video],[Slides].
  Not numbers, not text. Categorical variables handle a controlled vocabulary to avoid errors and simplify the analysis.
• Class 21: Exploring data with plots. (Dec 21, 2020). [Video],[Slides].
  There are several ways to do graphics in R. In this class we will show the basic graphic commands.
• Class 22: Linear models. (Dec 28, 2020). [Video],[Slides].
  Finding the best fitting straight line. See also:
  • Coil extension data.
  • Speed of sound data.
  • Practical exercise.
• Class 23: Logarithmic scales. (Dec 28, 2020). [Video],[Slides].
  Like Robin Hood, logarithms enlarge small values and reduce big values. Logarithmic scales are microscopes and telescopes at the same time. What does it mean for you? See also:
  • Data supporting Moore’s law.
  • Historic DNA sequencing costs.
• Class 24: Logarithmic models. (Jan 4, 2021). [Video],[Slides].
  Not all lines are straight lines. But they can be straight if you change your perspective. See also:
  • Data from Kleiber’s paper.
• Class 25: Polynomial Models. (Jan 4, 2021). [Video],[Slides].
  Not all lines are straight lines, or exponentials, or power laws. See also:
  • Size of Genomic databases.
  • Video of Free fall experiment, replica A.
  • Video of Free fall experiment, replica B.
• Class 26: Drawing beautiful plots. (Jan 11, 2021). [Video],[Slides].
  The grammar of graphics. See also:
  • An introduction to R Graphics. ggplot2.
  • ggplot2 Quick Reference.
  • R intro, by Karel Fišer.
  • Introduction to ggplot2.
  • Statistical tools for high-throughput data analysis: ggplot2 essentials.
• Class 27: More beautiful plots. (Jan 11, 2021). [Video],[Slides].
  The grammar of graphics. Multiple lines. See also:
  • Practice Class 27.
• Class 28: Linear models with factors. (Jan 18, 2021). [Video],[Slides].
  Useful for gene expression analysis. See also:
  • Solution of Midterm exam.

Attendance

By regulation from the Rectory, students need to attend at least 70% of the classes. The attendance book is updated every week and can be seen in Google Sheets.

To be counted as present, you must answer a Quiz during the class time and deliver all homework on time. Late submissions will not be accepted.

Some Online Resources

Video Material

Required software

For this course we will use the new version of R and Rstudio. These two tools work together. Install R first, then install Rstudio.

• Download and Install R
• Download RStudio

These videos may help you

• Install R and R Studio on Windows 10
• Installing R version 4.0 + RTools 4.0 + RStudio For Data Science
• Installing R and RStudio on Windows 10

Course Forum

Once you have registered for the forum, you should send all your questions by email to iu-cmb@googlegroups.com. You can also write your questions, and check for previous messages, on the web page https://groups.google.com/d/forum/iu-cmb.

Welcome survey

Everybody must register to the course forum. To do so you must fill the Welcome survey and register your email address. I recommend that you use a gmail account, such as the ogr.iu.edu.tr email service provided by the university. In any case, use an email address that you check regularly. We will use this forum to send important material.

Online learning

This semester we will carry on the course online. That is an interesting challenge, since it makes some things harder but others simpler. To start, everybody should read this paper:

Searls DB. “Ten simple rules for online learning”. PLoS Computational Biology. 2012;8(9):e1002631. DOI: 10.1371/journal.pcbi.1002631. Epub 2012 Sep 13. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3441493/

Recommended readings

• Frey, Carl Benedikt, and Michael A Osborne. “The Future of Employment: How Susceptible Are Jobs to Computerisation?” Technological Forecasting and Social Change 114 (January 2017): 254–80. https://doi.org/10.1016/j.techfore.2016.08.019.

• Nuzzo, Regina. “How Scientists Fool Themselves – and How They Can Stop.” Nature 526, no. 7572 (2015): 182–85. https://doi.org/10.1038/526182a.

• Polya, G. and Conway, John H. “How to Solve It: A New Aspect of Mathematical Method.” Princeton Science Library.