Bioinformatics

<div align="center"> <img src="http://i.imgur.com/kYYCXtC.png" alt="Open Source Society logo"/> <h3>Open Source Society University</h3> <p> :microscope: Path to a free self-taught education in <strong>Bioinformatics!</strong> </p> <p> <a href="https://github.com/open-source-society/bioinformatics"> <img alt="Open Source Society University - Bioinformatics" src="https://img.shields.io/badge/OSSU-bioinformatics-blue.svg"> </a> </p> <p> <h3> Archived </h3> </p> </div>

Note: this curriculum is not under active development and may be out of date. Read more here.

Contents

• About
• Motivation & Preparation
• Curriculum
• How to use this guide
• Prerequisite
• How to collaborate
• Code of Conduct
• Community
• Team
• References

About

This is a solid path for those of you who want to complete a Bioinformatics course on your own time, for free, with courses from the best universities in the World.

In our curriculum, we give preference to MOOC (Massive Open Online Course) style courses because these courses were created with our style of learning in mind.

To become a bioinformatician, you have to learn quite a lot of science, so be ready for subjects like; Biology, Chemistry, etc...

Motivation & Preparation

Here are two interesting links that can make all the difference in your journey.

The first one is a motivational video that shows a guy that went through the "MIT Challenge", which consists of learning the entire 4-year MIT curriculum for Computer Science in 1 year.

• MIT Challenge

The second link is a MOOC that will teach you learning techniques used by experts in art, music, literature, math, science, sports, and many other disciplines. These are fundamental abilities to succeed in our journey.

• Learning How to Learn

Are you ready to get started?

Curriculum

1st Year

Code | Course | Duration | Effort :-- | :--: | :--: | :--: BIO 1311 | Fundamentals of Biology | 12 weeks | 7-14 Hours/Week CHEM 1311 | Principles of Chemical Science | 15 Weeks | 4-6 Hours/Week Py4E | Python for Everybody | 10 weeks | 10 hours/week 6.00.1x | Introduction to Computer Science and Programming using Python (alt) | 9 weeks | 15 hours/week MATH 1311 | College Algebra and Problem Solving | 4 Weeks | 6 Hours/Week MATH 1312 | Pre-calculus | 4 Weeks | 6 Hours/Week 18.01.1x | Calculus 1A: Differentiation | 13 weeks | 6-10 hours/week 18.01.2x | Calculus 1B: Integration | 13 weeks | 5-10 hours/week MATH 1315 | Introduction to Probability and Data (with R) | 5 Weeks | 6 Hours/Week

2nd Year

Code | Course | Duration | Effort :-- | :--: | :--: | :--: BIO 2311 | Biochemistry | 15 Weeks | 4-6 Hours/Week CHEM 2311 | Organic Chemistry | 15 Weeks | 4-6 Hours/Week COMP 2311 | CS 2 - Object Oriented Java | 6 Weeks | 4-6 Hours/Week 18.01.3x | Calculus 1C: Coordinate Systems & Infinite Series | 6 weeks | 5-10 hours/week 6.042J | Mathematics for Computer Science (Solutions) | 13 weeks | 5 hours/week COMP 2312 | Databases | 10 Weeks | 8-12 Hours/Week 18.06 | Linear Algebra and Essence of Linear Algebra | 14 weeks | 12 hours/week COMP 2313 | Introduction to Linux | 8 Weeks | 5-7 Hours/Week MATH 2314 | Inferential Statistics (with R) | 5 Weeks | 6 Hours/Week

3rd Year

Code | Course | Duration | Effort :-- | :--: | :--: | :--: BIO 3311 | Proteins' Biology | 5 Weeks | 4-6 Hours/Week COMP 3311a | Algorithmic Thinking 1 | 4 Weeks | 6 Hours/Week COMP 3311b | Algorithmic Thinking 2 | 4 Weeks | 6 Hours/Week MATH 3311 | Linear Regression and Modeling (with R)| 4 Weeks | 6 Hours/Week MATH 3312 | Bayesian Statistics (with R) | 5 Weeks | 6 Hours/Week BIO 3312 | Cell Biology | - Weeks | - Hours/Week MATH 3313 | Differential Equations | 7 Weeks | 8-10 Hours/Week BIO 3313a | Biostatistics 1 | 4 Weeks | 3-5 Hours/Week BIO 3313b | Biostatistics 2 | 4 Weeks | 3-5 Hours/Week

4th Year

Code | Course | Duration | Effort :-- | :--: | :--: | :--: BIO 4311 | DNA: Biology's Genetic Code | 6 Weeks | 4-6 Hours/Week COMP 4311 | Data Science | 13 Week | 10 Hours/Week BIO 4312a | Molecular Biology | 16 Weeks | 4-8 Hours/Week BIO 4312d | Bioinformatics 1 | 4 Weeks | 4-10 Hours/Week COMP 4312a | Bioinformatics 2 | 4 Week | 6 Hours/Week COMP 4312b | Bioinformatics 3 | 4 Week | 6 Hours/Week COMP 4312c | Bioinformatics 4 | 4 Week | 6 Hours/Week COMP 4312d | Bioinformatics 5 | 4 Week | 6 Hours/Week COMP 4312e | Bioinformatics 6 | 4 Week | 6 Hours/Week COMP 4312f | Bioinformatics 7 (Capstone) | 3 Week | 3-4 Hours/Week BIO 4313 | Evolution | 11 Weeks | 4-6 Hours/Week

Extra Year

Code | Course | Duration | Effort :-- | :--: | :--: | :--: COMP 5311 | Introduction to Machine Learning | 10 Weeks | 6 Hours/Week COMP 5312 | Deep Learning | 8 Weeks | 6 Hours/Week Extension | Genomic Data Science Specialization | 32 Week | 6 Hours/Week

Will continue with Master's in Bioinformatics

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How to use this guide

Order of the classes

This guide was developed to be consumed in a linear approach. What does this mean? That you should complete one course at a time.

The courses are already in the order that you should complete them. Just start the first course, Introduction to Biology, when you done with it, start the next one.

If the course is not open, do it with the archived resources or wait until next class is open.

How to track and show your progress

1. Create an account in Trello.
2. Copy this board to your personal account. See how to copy a board here.

Now that you have a copy of our official board, you just need to pass the cards to the Doing column or Done column as you progress in your study.

We also have labels to help you have more control through the process. The meaning of each of these labels is:

• Main Curriculum: cards with that label represent courses that are listed in our curriculum.
• Extra Courses: cards with that label represent courses that was added by the student.
• Doing: cards with that label represent courses the student is current doing.
• Done: cards with that label represent courses finished by the student. Those cards should also have the link for at least one project/article built with the knowledge acquired in such course.
• Section: cards with that label represent the section that we have in our curriculum. Those cards with the Section label are only to help the organization of the Done column. You should put the Course's cards below its respective Section's card.
• Extra Sections: cards with that label represent sections that was added by the student.

The intention of this board is to provide for our