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A summary of the lecture and possible exam questions for Protein Predictions course at TUM.

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Protein Prediction I

Course Summary, Summer Term 2017

tl;dr: The purpose of this document to collaborativeley create a both concise and detailed course summary of the _Protein Prediction I _ Lecture from 2017 Summer Term at TUM.

To learn as effective as possible, I would like to encourage everyone to engage in the discussion evolving around the content of this document. If you have questions or challenge what someone else wrote please do so in a constructive way. We are all new to the subject of Protein Prediction and mistakes happen. Let's learn from them together!

Official Lecture Resources

Lecture Homepage: https://www.rostlab.org/teaching/ss17/pp1cs

Lecture Wiki: https://i12r-studfilesrv.informatik.tu-muenchen.de/sose17/pp4cs1/index.php/Main_Page

Youtube Channel: https://www.youtube.com/channel/UCU6j8BG4RbEtTgyIZJ6Vpow

Getting Started

This document is set up a Gitbook and hosted on Github. When you read this, you were already granted access to the repository so the first step is done.

The easist way to start contributing is to download **Gitbook Editor **(available for Mac, Linux, Windows) from here.

Before you add / change anything, please read through the Contribution Guide.

Contribution Guide

Tell others what you work on | Write meaningful commit messages | Push often | Use American English

Why is there a contribution guide? I think it is in everyone's best interest to keep this summary as easy to understand as possible for everyone. This guideline should help to maintain consistency across the entire document.

Each section may contain a short additional information on how to format things specific to that section. Please have a look there as well.

1. Adding new content

1.1 Adding minor updates

If you add minor updates, like the answer to a single question, you can do this on the develop branch directly. Make sure your commit has a meaningful message.

1.2 Adding major updates

If you add major updates, like several related changes (e.g. an entire lecture summary), go along as follows:

  1. Add a new issue on Github, describing what you are working on
  2. Create a feature/<issue-name>branch and add your changes
  3. Open a pull-request to merge back into developand add the other contributers as reviewers
  4. Once the pull request is merged, delete your feature branch and close the issue by referencing the merge commit

**Why so complicated? **This way the issues reflect new changes and are transparent for all contributors.

2. Challenging existing content

If you find obvious mistakes (typos, clearly wrong statements) just change them directly.

If you are challenging statements, answers to questions etc. which might not be trivial to understand go along as follows:

  1. Open a new issue on github.
  2. Reference the the statement in question you consider to be wrong
  3. Provide an explanation why you think it is wrong
  4. Provide your correct solution.

3. Adding new contributors

The purpose of this document is to foster collaborative learning - hence to make this as inclusive as possible. This being said, too many collaborators would probably lead to chaos 💥. If you know other students personally, you want to add to the project shoot me a message and we will figure it out.

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A summary of the lecture and possible exam questions for Protein Predictions course at TUM.

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