[ { "path": "ARCHIVED.md", "content": "# Archived\nThis curriculum has been archived.\nNo issues will be addressed and no pull requests merged in.\nNo changes will be made to the curriculum going forward.\n\n## Reason\nOSSU relies on a community of experts and learners to develop our curricula.\nThis is ongoing work, which requires evaluating new course offerings,\nreplacing courses that are discontinued, \nand responding to updated learning expectations of the field.\n\nUnfortunately, OSSU no longer has volunteers to undertake that work for this curriculum.\n\n## Unarchiving Criteria\nThis curriculum can be unarchived by a volunteer for curriculum maintainer.\nSuch a volunteer should contact the directors with:\n\n1. A proposed curricular guide.\n A stranger who reads the guide should have a clear idea of how to evaluate if a course will fit in the curriculum.\n It is generally easier to make such judgements if there is one curricular guide, a reason that the OSSU CS curriculum changed from having two to one a number of years ago.\n [This open issue](https://github.com/ossu/bioinformatics/issues/28) may be of assistance.\n2. An explanation of personal expertise.\n The maintainer must have demonstrated more than familiarity with bioinformatics.\n3. A pledge to be involved for at least 2 years.\n Maintaining the curriculum is a rewarding and long term commitment.\n4. A transition plan for the end-of-tenure.\n The last job of a great leader is to establish another great leader in their place.\n What steps will you take when you decide to step down to ensure that another maintainer is prepared to take over?\n\nYou can reach out to the directors by sending a message in the [server suggestions](https://discord.gg/ZQ2KRzU44D)\nchannel of the OSSU discord.\nUse `@directors` in your message.\nA director will start a private thread with you.\n" }, { "path": "README.md", "content": "
\n\"Open\n

Open Source Society University

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\n :microscope: Path to a free self-taught education in Bioinformatics!\n

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\n Archived\n

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\n\nNote: this curriculum is not under active development and may be out of date. Read more [here](./ARCHIVED.md).\n\n## Contents\n\n- [About](#about)\n- [Motivation & Preparation](#motivation--preparation)\n- [Curriculum](#curriculum)\n- [How to use this guide](#how-to-use-this-guide)\n- [Prerequisite](#prerequisite)\n- [How to collaborate](#how-to-collaborate)\n- [Code of Conduct](#code-of-conduct)\n- [Community](#community)\n- [Team](#team)\n- [References](#references)\n\n## About\n\nThis is a **solid path** for those of you who want to complete a [Bioinformatics](https://en.wikipedia.org/wiki/Bioinformatics) course on your own time, **for free**, with courses from the **best universities** in the World.\n\nIn 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.\n\nTo become a bioinformatician, you have to learn quite a lot of science, so be ready for subjects like; Biology, Chemistry, etc...\n\n## Motivation & Preparation\n\nHere are two interesting links that can make **all** the difference in your journey.\n\nThe 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**.\n\n- [MIT Challenge](https://www.scotthyoung.com/blog/myprojects/mit-challenge-2/)\n\nThe 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.\n\n- [Learning How to Learn](https://www.coursera.org/learn/learning-how-to-learn)\n\n**Are you ready to get started?**\n\n## Curriculum\n\n### 1st Year\n\nCode | Course | Duration | Effort\n:-- | :--: | :--: | :--:\nBIO 1311 | [Fundamentals of Biology](https://ocw.mit.edu/courses/7-01sc-fundamentals-of-biology-fall-2011/) | 12 weeks | 7-14 Hours/Week\nCHEM 1311 | [Principles of Chemical Science](https://ocw.mit.edu/courses/5-111sc-principles-of-chemical-science-fall-2014/) | 15 Weeks | 4-6 Hours/Week\nPy4E | [Python for Everybody](https://www.py4e.com/lessons) | 10 weeks | 10 hours/week\n6.00.1x | [Introduction to Computer Science and Programming using Python](https://ocw.mit.edu/courses/6-0001-introduction-to-computer-science-and-programming-in-python-fall-2016/) ([alt](https://www.edx.org/course/introduction-to-computer-science-and-programming-7)) | 9 weeks | 15 hours/week\nMATH 1311 | [College Algebra and Problem Solving](https://www.edx.org/course/college-algebra-problem-solving-asux-mat117x) | 4 Weeks | 6 Hours/Week\nMATH 1312 | [Pre-calculus](https://www.edx.org/course/precalculus-asux-mat170x) | 4 Weeks | 6 Hours/Week\n18.01.1x | [Calculus 1A: Differentiation](https://openlearninglibrary.mit.edu/courses/course-v1:MITx+18.01.1x+2T2019/about) | 13 weeks | 6-10 hours/week\n18.01.2x | [Calculus 1B: Integration](https://openlearninglibrary.mit.edu/courses/course-v1:MITx+18.01.2x+3T2019/about) | 13 weeks | 5-10 hours/week\nMATH 1315 | [Introduction to Probability and Data (with R)](https://www.coursera.org/learn/probability-intro) | 5 Weeks | 6 Hours/Week\n\n\n### 2nd Year\n\nCode | Course | Duration | Effort\n:-- | :--: | :--: | :--:\nBIO 2311 | [Biochemistry](https://www.edx.org/course/principles-of-biochemistry) | 15 Weeks | 4-6 Hours/Week\nCHEM 2311 | [Organic Chemistry](http://ocw.mit.edu/courses/chemistry/5-12-organic-chemistry-i-spring-2005/) | 15 Weeks | 4-6 Hours/Week\nCOMP 2311 | [CS 2 - Object Oriented Java](https://www.coursera.org/learn/object-oriented-java) | 6 Weeks | 4-6 Hours/Week\n18.01.3x | [Calculus 1C: Coordinate Systems & Infinite Series](https://openlearninglibrary.mit.edu/courses/course-v1:MITx+18.01.3x+1T2020/about) | 6 weeks | 5-10 hours/week\n6.042J | [Mathematics for Computer Science](https://openlearninglibrary.mit.edu/courses/course-v1:OCW+6.042J+2T2019/about) ([Solutions](https://github.com/spamegg1/Math-for-CS-solutions)) | 13 weeks | 5 hours/week\nCOMP 2312 | [Databases](https://online.stanford.edu/courses/soe-ydatabases-databases) | 10 Weeks | 8-12 Hours/Week\n18.06 | [Linear Algebra](https://ocw.mit.edu/courses/mathematics/18-06sc-linear-algebra-fall-2011/) and [Essence of Linear Algebra](https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab) | 14 weeks | 12 hours/week\nCOMP 2313 | [Introduction to Linux](https://www.edx.org/course/introduction-linux-linuxfoundationx-lfs101x-0) | 8 Weeks | 5-7 Hours/Week\nMATH 2314 | [Inferential Statistics (with R)](https://www.coursera.org/learn/inferential-statistics-intro) | 5 Weeks | 6 Hours/Week\n\n### 3rd Year\n\nCode | Course | Duration | Effort\n:-- | :--: | :--: | :--:\nBIO 3311 | [Proteins' Biology](https://www.edx.org/course/proteins-biologys-workforce) | 5 Weeks | 4-6 Hours/Week\nCOMP 3311a | [Algorithmic Thinking 1 ](https://www.coursera.org/learn/algorithmic-thinking-1) | 4 Weeks | 6 Hours/Week\nCOMP 3311b | [Algorithmic Thinking 2 ](https://www.coursera.org/learn/algorithmic-thinking-2) | 4 Weeks | 6 Hours/Week\nMATH 3311 | [Linear Regression and Modeling (with R)](https://www.coursera.org/learn/linear-regression-model)| 4 Weeks | 6 Hours/Week\nMATH 3312 | [Bayesian Statistics (with R)](https://www.coursera.org/learn/bayesian) | 5 Weeks | 6 Hours/Week\nBIO 3312 | [Cell Biology ](http://ocw.mit.edu/courses/biology/7-06-cell-biology-spring-2007/) | - Weeks | - Hours/Week\nMATH 3313 | [Differential Equations](https://ocw.mit.edu/courses/mathematics/18-03sc-differential-equations-fall-2011/) | 7 Weeks | 8-10 Hours/Week\nBIO 3313a | [Biostatistics 1](https://www.coursera.org/learn/biostatistics) | 4 Weeks | 3-5 Hours/Week\nBIO 3313b | [Biostatistics 2](https://www.coursera.org/learn/biostatistics-2) | 4 Weeks | 3-5 Hours/Week\n\n\n### 4th Year\n\nCode | Course | Duration | Effort\n:-- | :--: | :--: | :--:\nBIO 4311 | [DNA: Biology's Genetic Code](https://www.edx.org/course/dna-biologys-genetic-code) | 6 Weeks | 4-6 Hours/Week\nCOMP 4311 | [Data Science ](http://cs109.github.io/2015/) | 13 Week | 10 Hours/Week\nBIO 4312a | [Molecular Biology](https://ocw.mit.edu/courses/biology/7-28-molecular-biology-spring-2005/) | 16 Weeks | 4-8 Hours/Week\nBIO 4312d | [Bioinformatics 1](https://www.coursera.org/learn/dna-analysis) | 4 Weeks | 4-10 Hours/Week\nCOMP 4312a | [Bioinformatics 2](https://www.coursera.org/learn/genome-sequencing) | 4 Week | 6 Hours/Week\nCOMP 4312b | [Bioinformatics 3](https://www.coursera.org/learn/comparing-genomes) | 4 Week | 6 Hours/Week\nCOMP 4312c | [Bioinformatics 4](https://www.coursera.org/learn/molecular-evolution) | 4 Week | 6 Hours/Week\nCOMP 4312d | [Bioinformatics 5](https://www.coursera.org/learn/genomic-data) | 4 Week | 6 Hours/Week\nCOMP 4312e | [Bioinformatics 6](https://www.coursera.org/learn/dna-mutations) | 4 Week | 6 Hours/Week\nCOMP 4312f | [Bioinformatics 7 (Capstone)](https://www.coursera.org/learn/bioinformatics-project) | 3 Week | 3-4 Hours/Week\nBIO 4313 | [Evolution](https://www.coursera.org/learn/genetics-evolution) | 11 Weeks | 4-6 Hours/Week\n\n\n### Extra Year\n\nCode | Course | Duration | Effort\n:-- | :--: | :--: | :--:\nCOMP 5311 | [Introduction to Machine Learning](https://www.udacity.com/course/intro-to-machine-learning--ud120) | 10 Weeks | 6 Hours/Week\nCOMP 5312 | [Deep Learning](https://www.udacity.com/course/deep-learning--ud730) | 8 Weeks | 6 Hours/Week\nExtension | [Genomic Data Science Specialization](https://www.coursera.org/specializations/genomic-data-science) | 32 Week | 6 Hours/Week \n\n\n> Will continue with Master's in Bioinformatics\n\n\n---\n\n![keep learning](http://i.imgur.com/REQK0VU.jpg)\n\n## How to use this guide\n\n### Order of the classes\n\nThis guide was developed to be consumed in a linear approach. What does this mean? That you should complete one course at a time.\n\nThe courses are **already** in the order that you should complete them. Just start the first course, [Introduction to Biology](https://www.edx.org/course/introduction-biology-secret-life-mitx-7-00x-2), when you done with it, start the next one.\n\n**If the course is not open, do it with the archived resources or wait until next class is open.**\n\n### How to track and show your progress\n\n1. Create an account in [Trello](https://trello.com/).\n1. Copy [this](https://trello.com/b/yax8Kgnh) board to your personal account. See how to copy a board [here](http://blog.trello.com/you-can-copy-boards-now-finally/).\n\nNow 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.\n\nWe also have **labels** to help you have more control through the process. The meaning of each of these labels is:\n\n- `Main Curriculum`: cards with that label represent courses that are listed in our curriculum.\n- `Extra Courses`: cards with that label represent courses that was added by the student.\n- `Doing`: cards with that label represent courses the student is current doing.\n- `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.\n- `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*.\n- `Extra Sections`: cards with that label represent sections that was added by the student.\n\nThe intention of this board is to provide for our students a way to track their progress, and also the ability to show their progress through a public page for friends, family, employers, etc. You can change the status of your board to be **public** or **private**.\n\n\n\n### Should I take all courses?\n\n**Yes!** The intention is to conclude **all** the courses listed here! Also we highly encourage you to complete more by reading papers and attending research projects after your coursework is done.\n\n### Duration of the course\n\nIt may take longer to complete all of the classes compared to a regular Bioinformatics course, but we can **guarantee** you that your **reward** will be proportional to **your motivation/dedication**!\n\nYou must focus on your **habit**, and **forget** about goals. Try to invest 1 ~ 2 hours **every day** studying this curriculum. If you do this, **inevitably** you'll finish this curriculum.\n\n> See more about \"Commit to a process, not a goal\" [here](http://jamesclear.com/goals-systems).\n\n### Project Based\n\nHere in **OSS University**, you do **not** need to take exams, because we are focused on **real projects**!\n\nIn order to show for everyone that you **successfully** finished a course, you should create a **real project** or write **papers and publish them** about your focus with Bioinformatics.\n\n> \"What does it mean?\"\n\nAfter finish a course, you should think about a **real world problem** that you can solve using the acquired knowledge in the course. You don't need to create a big project, but you must create something to **validate** and **consolidate** your knowledge, and also to show to the world that you are capable to create something useful with the concepts that you learned.\n\n Put the OSSU-Bioinformatics badge in the README of your repository! [![Open Source Society University - Bioinformatics](https://img.shields.io/badge/OSSU-bioinformatics-blue.svg)](https://github.com/open-source-society/bioinformatics)\n\n - Markdown: `[![Open Source Society University - Bioinformatics ](https://img.shields.io/badge/OSSU-bioinformatics-blue.svg)](https://github.com/open-source-society/bioinformatics)`\n - HTML: `\"Open`\n\n**You can create this project alone or with other students!**\n\n### Be creative!\n\nThis is a **crucial** part of your journey through all those courses.\n\nYou **need** to have in mind that what you are able to **create** with the concepts that you learned will be your certificate **and this is what really matters**!\n\nIn order to show that you **really** learned those things, you need to be **creative**!\n\nHere are some tips about how you can do that:\n\n- **Articles**: create blog posts to synthesize/summarize what you learned.\n- **GitHub repository**: keep your course's files organized in a GH repository, so in that way other students can use it to study with your annotations.\n\n### Cooperative work\n\n**We love cooperative work**! Use our [channels](#community) to communicate with other fellows to combine and create new projects!\n\n### Which programming languages should I use?\n\nList of skills:\n- C/C++\n- Unix System\n- Python/Perl\n- R\n- Algorithms\n\nThese skills mentioned above are the very essential tool set that bioinformatician and computational biologist depends on.\n\nThe **important** thing for each course is to **internalize** the **core concepts** and to be able to use them with whatever tool (programming language) that you wish.\n\n### Content Policy\n\nYou must share **only** files that you are **allowed** to! **Do NOT disrespect the code of conduct** that you signed in the beginning of some courses.\n\n[Be creative](#be-creative) in order to show your progress! :smile:\n\n### Stay tuned\n\n[Watch](https://help.github.com/articles/watching-repositories/) this repository for futures improvements and general information.\n\n## Prerequisite\n\nStudents without a strong high school background in Biology will benefit from [Getting up to Speed in Biology](https://openlearninglibrary.mit.edu/courses/course-v1:OCW+Pre-7.01+1T2020/about).\n\nUnderstanding how to use Git to version your work can be hugely beneficial and is generally not taught in other courses. [Version Control with Git](https://www.udacity.com/course/version-control-with-git--ud123) should get you up to speed.\n\n## How to collaborate\n\nYou can [open an issue](https://help.github.com/articles/creating-an-issue/) and give us your suggestions as to how we can improve this guide, or what we can do to improve the learning experience.\n\nYou can also [fork this project](https://help.github.com/articles/fork-a-repo/) and send a [pull request](https://help.github.com/articles/using-pull-requests/) to fix any mistakes that you have found.\n\nTODO:\nIf you want to suggest a new resource, send a pull request adding such resource to the [extras](https://github.com/open-source-society/bioinformatics/tree/master/extras) section.\n\nThe **extras** section is a place where all of us will be able to submit interesting additional articles, books, courses and specializations, keeping our curriculum *as immutable and concise as possible*.\n\n**Let's do it together! =)**\n\n## Code of conduct\n\n[OSSU's code of conduct](https://github.com/ossu/code-of-conduct).\n\n## Community\n\nWe have a Discord server! This should be your first stop to talk with other OSSU students. [Why don't you introduce yourself right now?](https://discord.gg/wuytwK5s9h)\n\nSubscribe to our [newsletter](https://tinyletter.com/OpenSourceSocietyUniversity)\n\nYou can also interact through [GitHub issues](https://github.com/open-source-society/bioinformatics/issues).\n\nAdd **Open Source Society University** to your [Linkedin](https://www.linkedin.com/school/11272443/) and join our [Facebook](https://www.facebook.com/groups/opensourcesocietyu/) group!\n\n## Team\n\n* **Curriculum Founder**: [Enes Kemal Ergin](https://github.com/eneskemalergin)\n* **Curriculum Maintainer**: [Enes Kemal Ergin](https://github.com/eneskemalergin)\n* **Contributors**: [contributors](https://github.com/open-source-society/bioinformatics/graphs/contributors)\n\n## References\n" }, { "path": "Subject_Domains.md", "content": "## Subject Domains for Bioinformatics Education\n\n### Biology\nCode | Course | Duration | Effort\n:-- | :--: | :--: | :--:\nBIO 1311 | [Introduction to Biology](https://www.edx.org/course/introduction-biology-secret-life-mitx-7-00x-2) | 12 weeks | 7-14 Hours/Week\nBIO 2311 | [Biochemistry](https://www.edx.org/course/principles-biochemistry-harvardx-mcb63x) | 15 Weeks | 4-6 Hours/Week\nBIO 3311 | [Genetics 1 ](https://www.edx.org/course/useful-genetics-part-1-how-genes-shape-ubcx-usegen-1x-0) | 7 Weeks | 6-8 Hours/Week\nBIO 3312 | [Cell Biology ](http://ocw.mit.edu/courses/biology/7-06-cell-biology-spring-2007/) | - Weeks | - Hours/Week\nBIO 3313a | [Biostatistics 1](https://www.coursera.org/learn/biostatistics) | 4 Weeks | 3-5 Hours/Week\nBIO 3313b | [Biostatistics 2](https://www.coursera.org/learn/biostatistics-2) | 4 Weeks | 3-5 Hours/Week\nBIO 4311 | [Genetics 2](https://www.edx.org/course/useful-genetics-part-2-genes-genetic-ubcx-usegen-2x-0) | 5 Weeks | 6-8 Hours/Week\nBIO 4312a | [Molecular Biology 1 ](https://www.edx.org/course/molecular-biology-part-1-dna-replication-mitx-7-28-1x1-0) | 8 Weeks | 4-8 Hours/Week\nBIO 4312b | [Molecular Biology 2 ](https://www.edx.org/course/molecular-biology-part-2-transcription-mitx-7-28-2x-0) | 6 Weeks | 4-8 Hours/Week\nBIO 4312c | [Molecular Biology 3](https://www.edx.org/course/molecular-biology-part-3-rna-processing-mitx-7-28-3x-0) | 8 Weeks | 4-8 Hours/Week\nBIO 4312d | [Basic Bioinformatics (Bioinformatics 1)](https://www.coursera.org/learn/bioinformatics) | 4 Weeks | 4-6 Hours/Week\nBIO 4313a | [Evolution](https://www.coursera.org/learn/genetics-evolution) | 11 Weeks | 4-6 Hours/Week\n\n### Chemistry\nCode | Course | Duration | Effort\n:-- | :--: | :--: | :--:\nCHEM 1311 | [Principles of Chemistry](http://ocw.mit.edu/courses/chemistry/5-111-principles-of-chemical-science-fall-2008/) | 15 Weeks | 4-6 Hours/Week\nCHEM 2311 | [Organic Chemistry](http://ocw.mit.edu/courses/chemistry/5-12-organic-chemistry-i-spring-2005/) | 15 Weeks | 4-6 Hours/Week\n\n### Computer Science\nCode | Course | Duration | Effort\n:-- | :--: | :--: | :--:\nCOMP 1311a | [CS 1 - Python 1 ](https://www.coursera.org/learn/interactive-python-1) | 5 Weeks | 6 Hours/Week\nCOMP 1311b | [CS 1 - Python 2 ](https://www.coursera.org/learn/interactive-python-2) | 4 Weeks | 6 Hours/Week\nCOMP 1311c | [CS 1 - Principles of Computing 1 ](https://www.coursera.org/learn/principles-of-computing-1) | 4 Weeks | 6 Hours/Week\nCOMP 1311d | [CS 1 - Principles of Computing 2 ](https://www.coursera.org/learn/principles-of-computing-2) | 4 Weeks | 6 Hours/Week\nCOMP 2311 | [CS 2 - Object Oriented Java](https://www.coursera.org/learn/object-oriented-java) | 6 Weeks | 4-6 Hours/Week\nCOMP 2312 | [Introduction to Databases](https://lagunita.stanford.edu/courses/Engineering/db/2014_1/about) | 10 Weeks | 8-12 Hours/Week\nCOMP 2313 | [Introduction to Linux](https://www.edx.org/course/introduction-linux-linuxfoundationx-lfs101x-0) | 8 Weeks | 5-7 Hours/Week\nCOMP 3311a | [Algorithmic Thinking 1 ](https://www.coursera.org/learn/algorithmic-thinking-1) | 4 Weeks | 6 Hours/Week\nCOMP 3311b | [Algorithmic Thinking 2 ](https://www.coursera.org/learn/algorithmic-thinking-2) | 4 Weeks | 6 Hours/Week\nCOMP 3312 | [High Performance (?)]() | ? | ?\nCOMP 4311 | [Data Science ](http://cs109.github.io/2015/) | 13 Week | 10 Hours/Week\nCOMP 4312a | [Bioinformatics 2](https://www.coursera.org/learn/genome-sequencing) | 4 Week | 6 Hours/Week\nCOMP 4312b | [Bioinformatics 3](https://www.coursera.org/learn/comparing-genomes) | 4 Week | 6 Hours/Week\nCOMP 4312c | [Bioinformatics 4](https://www.coursera.org/learn/molecular-evolution) | 4 Week | 6 Hours/Week\nCOMP 4312d | [Bioinformatics 5](https://www.coursera.org/learn/genomic-data) | 4 Week | 6 Hours/Week\nCOMP 4312e | [Bioinformatics 6](https://www.coursera.org/learn/dna-mutations) | 4 Week | 6 Hours/Week\nCOMP 5311 | [Introduction to Machine Learning](https://www.udacity.com/course/intro-to-machine-learning--ud120) | 10 Weeks | 6 Hours/Week\nCOMP 5312 | [Deep Learning](https://www.udacity.com/course/deep-learning--ud730) | 8 Weeks | 6 Hours/Week\nExtension | [Genomic Data Science Specialization](https://www.coursera.org/specializations/genomic-data-science) | 32 Week | 6 Hours/Week \n\n### Math\nCode | Course | Duration | Effort\n:-- | :--: | :--: | :--:\nMATH 1311 | [Calculus 1](https://www.coursera.org/learn/calculus1) | 16 Weeks | 6 Hours/Week\nMATH 1312 | [Mathematics for CS](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-042j-mathematics-for-computer-science-fall-2010/index.htm) | 13 Weeks | 6 Hours/Week\nMATH 2311 | [Calculus 2](https://www.coursera.org/learn/advanced-calculus) | 8 Weeks | 6 Hours/Week\nMATH 2312 | [Linear Algebra](https://www.edx.org/course/linear-algebra-foundations-frontiers-utaustinx-ut-5-04x) | 15 Weeks | 8 Hours/Week\nMATH 2313 | [Descriptive Statistics](https://www.edx.org/course/introduction-statistics-descriptive-uc-berkeleyx-stat2-1x#!) | 5 Weeks | 8 Hours/Week\nMATH 3311 | [Probability](https://www.edx.org/course/introduction-statistics-probability-uc-berkeleyx-stat2-2x)| 5 Weeks | 8 Hours/Week\nMATH 3312 | [Differential Equations](https://www.edx.org/course/introduction-differential-equations-bux-math226-1x-0) | 7 Weeks | 8-10 Hours/Week\nMATH 4311 | [Inferential Statistics](https://www.edx.org/course/introduction-statistics-inference-uc-berkeleyx-stat2-3x) | 5 Weeks | 8 Hours/Week\n\n\n### Master Courses\n- Choose your Path\n- Systems Biology\n- Computational Biology\n- Bioinformatics\n- Computational Neuroscience\n- Biomedical Engineering\n> More here...\n" }, { "path": "To-Do.md", "content": "# To-Do List for Bioinformatics\n\n- [x] Read the papers about online bioinformatics\n- [x] Itemize the topic requirements\n- [x] Search for other schools curriculum\n- [x] Search for the online education platforms\n- [x] Itemize the courses\n- [x] Order the courses\n- [ ] Prepare a reading list of textbooks\n- [ ] Extra reading, most recent papers on bioinformatics technologies\n- [ ] Search for all possible fields of studies (For mastery)\n- [ ] Find a domain of your interest, do your own research while learning ;-)\n" }, { "path": "extras/articles.md", "content": "# Bioinformatics - Extra Resources\n\n# Articles\n1. [So you want to be a computational biologist?](http://www.nature.com/nbt/journal/v31/n11/full/nbt.2740.html) by Nick Loman and Mick Watson (2013).\n1. [A Quick Guide for Developing Effective Bioinformatics Programming Skills](http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000589) by Joel Dudley and Atul Butte (2009).\n1. [Unix Philosophy](https://en.wikipedia.org/wiki/Unix_philosophy)\n" }, { "path": "extras/free-books.md", "content": "# Bioinformatics - Extra Resources\n\n# Free Books\n* [Molecular Biology of the Cell](https://www.ncbi.nlm.nih.gov/books/NBK21054/)\n* [An Introduction to Genetic Analysis](https://www.ncbi.nlm.nih.gov/books/NBK21766/)\n* [The GNU/Linux Command Line Interface (CLI)](http://linuxcommand.org/tlcl.php)\n* [Unix Grymoire](http://www.grymoire.com/)\n* [Algorithms and Data Structures](http://interactivepython.org/runestone/static/pythonds/index.html)\n* [Think like a Computer Scientist](http://interactivepython.org/runestone/static/thinkcspy/index.html)\n* [Data Analysis for the Life Sciences](https://leanpub.com/dataanalysisforthelifesciences)\n\n## Language Books\n* [Python](http://scipy.org/topical-software.html)\n * [Interactive Py](http://interactivepython.org/runestone/static/pythonds/index.html)\n * [Py For Biologists](http://pythonforbiologists.com/index.php/introduction-to-python-for-biologists/)\n * Quick applied language overview in [this workshop](https://swcarpentry.github.io/python-novice-inflammation/index.html)\n* Perl\n * [Perl 6](http://perl6intro.com/)\n * [Unix and Perl for Biologists](http://korflab.ucdavis.edu/Unix_and_Perl/index.html)\n* [Haskell](http://learnyouahaskell.com/chapters)\n* [Julia](http://julialang.org/learning/) ([book](https://en.wikibooks.org/wiki/Introducing_Julia))\n* [Make](http://www.oreilly.com/openbook/make3/book/index.csp) pipelines\n* R\n * [Data Analysis and Visualizations](http://varianceexplained.org/RData/)\n * Coursera JHU's [course notes](http://sux13.github.io/DataScienceSpCourseNotes/2_RPROG/R_Programming_Course_Notes.html)\n * Nail [lexical scoping](http://adv-r.had.co.nz/Functions.html#lexical-scoping)\n" }, { "path": "extras/free-courses.md", "content": "# Bioinformatics - Extra Resources\n\n# Free Courses\n\nPH525.1x: Statistics and R for the Life Sciences\n\nPH525.2x: Introduction to Linear Models and Matrix Algebra\n\nPH525.3x: Statistical Inference and Modeling for High-throughput Experiments\n\nPH525.4x: High-Dimensional Data Analysis\n\nPH525.5x: Introduction to Bioconductor: annotation and analysis of genomes and genomic assays\n\nPH525.6x: High-performance computing for reproducible genomics\n\nPH525.7x: Case studies in functional genomics\n\n## Workshops and tutorials mostly:\n* [Data Carpentry](http://www.datacarpentry.org/lessons/)\n* [OpenHelix](http://www.openhelix.com/freeTutorials.cgi)\n* [BioStars](https://www.biostars.org/t/Tutorials/)\n* [GenomeSpace Recipes](http://recipes.genomespace.org/home)\n* [EMBL-EBI](https://www.ebi.ac.uk/training/online/course-list)\n* [UC SantaCruz Training](https://genome.ucsc.edu/training/index.html)\n* [UC Davis Workshops](http://bioinformatics.ucdavis.edu/training/documentation/)\n* [InsideDNA Tutorials](https://insidedna.me/tutorials)\n* [Stephen Turner's list](http://stephenturner.us/edu.html)\n* [Griffith's RNA-seq](https://github.com/griffithlab/rnaseq_tutorial/wiki)\n* [NCBI Tutorials](http://www.ncbi.nlm.nih.gov/home/learn.shtml)\n* [Homolog.us Tutorials](http://homolog.us/Tutorials/)\n* [Broad Institute Medical and Population Genetics Primers](https://www.youtube.com/playlist?list=PLEEE2A91B09B77B4A)\n\n\n Try searching keywords like bioinformatics, biology, genomic, genetic, data analysis, data science, computer science, life science... in these websites:\n* [Coursera](https://www.coursera.org/)\n* [edX](https://www.edx.org/)\n* [MIT](http://ocw.mit.edu/courses)\n* [eBiomics](http://ebiomics.sdcinfo.com/)\n* [Khan Academy](http://www.khanacademy.org/)\n* [Udemy](http://www.udemy.com/)\n\n\n## Coding Courses and Tutorials\n* [Code Academy](https://www.codecademy.com/#!/exercises/0)\n* [Software Carpentry](http://software-carpentry.org/lessons/)\n* [Code Snipcademy](http://code.snipcademy.com)\n* [Udacity](https://www.udacity.com/)\n* [FreeCodeCamp](https://www.freecodecamp.com/)\n* Python\n * [Matplotlib](http://www.loria.fr/~rougier/teaching/matplotlib/) - Plotting\n * [Seaborn](https://web.stanford.edu/~mwaskom/software/seaborn/tutorial.html) - Plotting\n * [Pandas](http://pandas.pydata.org/pandas-docs/stable/) - Data Analysis\n * [Machine Learning](http://scikit-learn.org/stable/documentation.html) - Library\n * [HTSeq](http://www-huber.embl.de/users/anders/HTSeq/doc/overview.html) - Library\n* R\n * [Quick-R](http://www.statmethods.net/)\n * [Swirl](http://swirlstats.com/students.html)\n * [ggplot2](http://ggplot2.org/)\n * [R & NGS](http://manuals.bioinformatics.ucr.edu/home/ht-seq#TOC-SOAP)\n * [Bioconductor Lib](http://bioconductor.org/help/workflows/)\n * [RSeek Lib Search](http://www.rseek.org/)\n* Data Analysis Pipelines\n * GNU Make\n * [Dave Tang](http://davetang.org/muse/2015/05/31/learning-about-makefiles/)\n * [Stat545](http://stat545.com/automation04_make-activity.html)\n * [ZMJones](http://zmjones.com/make/)\n * [NextFlow](http://www.nextflow.io/docs/latest/index.html)\n * [SnakeMake](http://snakemake.bitbucket.org/snakemake-tutorial.html)\n" }, { "path": "extras/other-resources.md", "content": "# Handy Stuff\n* [UCSC FAQ](https://genome.ucsc.edu/FAQ/)\n* Rosalind [Glossary](http://rosalind.info/glossary/)\n* [Cheatsheets](http://overapi.com/)\n* [File Format Specifications](https://github.com/samtools/hts-specs)\n* [GATK](http://gatkforums.broadinstitute.org/gatk/categories)\n* [Genome Space](https://www.broadinstitute.org/scientific-community/science/projects/genomespace/genomespace)\n* [Writing your first academic paper](https://github.com/jtleek/firstpaper)\n* [Statistics for Biologists](http://www.nature.com/collections/qghhqm)\n* [another DS career, apart from the one of OSS](https://github.com/datasciencemasters/go)\n* [don't be a luser](http://www.catb.org/esr/faqs/smart-questions.html)\n* [here's the future](https://biojulia.github.io/Bio.jl/latest/)\n\n# Forums Q&A\n* [BioStars](https://www.biostars.org/)\n* [SEQAnswers](http://seqanswers.com/)\n* [SEQanswers - Bioinformatics](http://seqanswers.com/forums/external.php?type=RSS2&forumids=18)\n* [Bioinformatics subreddit](https://www.reddit.com/r/bioinformatics/)\n* [Bio Databases subreddit](http://www.reddit.com/r/BioDatasets)\n* [Genomic subreddit](http://www.reddit.com/r/genomics)\n* [Biology Q&A](https://biology.stackexchange.com/)\n* [Unix and GNU/Linux Q&A](https://unix.stackexchange.com/)\n* [Code Q&A](http://stackoverflow.com/)\n* [Ion Community](http://ioncommunity.lifetechnologies.com/community/)\n* [LinuxQuestions](http://www.linuxquestions.org/questions/)\n* [Bioconductor Q&A](https://support.bioconductor.org/)\n* [Statistics Q&A](http://stats.stackexchange.com/)\n* [Data Science Q&A](http://datascience.stackexchange.com/)\n\n# Wikis\n* [SEQAnswers](http://seqanswers.com/wiki/SEQanswers)\n* [GNU/Linux (Arch)Wiki](https://wiki.archlinux.org/)\n\n# Puzzles and Code Golf\n* [Code Golf](https://codegolf.stackexchange.com/)\n* [Project Euler](https://projecteuler.net/)\n* [Rosalind](http://rosalind.info/)\n* [Hacker Rank](https://www.hackerrank.com/domains/algorithms/warmup)\n\n# Other lists\n* [Bioinformatics Jobs](http://www.indeed.com/q-Bioinformatics-jobs.html)\n* [Biological Databases](https://en.wikipedia.org/wiki/List_of_biological_databases) (can't be up-to-date)\n* [Genomics Class](http://genomicsclass.github.io/book/pages/resources.html)\n* [HTS training materials repository](http://bioinformatics.upsc.se/htmr)\n* [Genomics Papers](https://github.com/jtleek/genomicspapers) by Leek Group\n* [Bioinformatics.org Educational Services](http://www.bioinformatics.org/wiki/Educational_services)\n* [ISCB courses](http://www.iscb.org/iscb-degree-certificate-programs)\n* Learning Programming Languages [[1]](http://hackr.io/) [[2]](https://github.com/vhf/free-programming-books)\n* Software\n * [bio-tools.org](https://bio-tools.org/)\n * [CCB at JHU](http://ccb.jhu.edu/software.shtml)\n * [Galaxy Toolshed](https://toolshed.g2.bx.psu.edu/)\n * [OMICtools](http://omictools.com/about)\n * [Sanger's Isntitute list](http://www.sanger.ac.uk/science/tools)\n\n# Illegal resources [you should avoid](http://www.sciencemag.org/news/2016/04/whos-downloading-pirated-papers-everyone)\n* Sci-Hub\n* LibGen\n* Bookfi\n\n**And always, enjoy [open culture](http://www.openculture.com/)**\n" }, { "path": "extras/paid-books.md", "content": "# Bioinformatics - Extra Resources\n\n# Paid Books\n* Biological Sequence Analysis (R. Durbin et al)\n* Bioinformatics and Functional Genomics (J. Pevsner)\n* BioInfoBook [Figures](http://bioinfbook.org/php/powerpoints)\n* [Bioinformatic Algorithms](http://bioinformaticsalgorithms.com/)\n" }, { "path": "extras/paid-courses.md", "content": "# Bioinformatics - Extra Resources\n\n# Paid Courses\n[Micro-masters in Bioinformatics from University of Maryland](https://www.edx.org/micromasters/bioinformatics)\n" }, { "path": "extras/softwares.md", "content": "# Bioinformatics - Extra Resources\n\n# Software Documentation\n* Install CLI tools with [BioConda](https://bioconda.github.io/) package manager\n* [Circos](http://circos.ca/documentation/course/)\n* [OpenGene Libraries](https://github.com/OpenGene)\n* [GATK Tools](https://www.broadinstitute.org/gatk/guide/tooldocs/index)\n* [ADAM](http://bdgenomics.org/) Big-Data Genomics\n* [FastQC](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/)\n* samtools 1:[BioBits'](http://biobits.org/samtools_primer.html) 2:[DaveTang's](https://github.com/davetang/learning_bam_file) 3:[YanhuiFan's](https://felixfan.github.io/bam-sam/) 4:[BinaryFlags](https://broadinstitute.github.io/picard/explain-flags.html)\n* [bcftools](https://samtools.github.io/bcftools/howtos/variant-calling.html) 1:[GATK](http://gatkforums.broadinstitute.org/gatk/discussion/1268/what-is-a-vcf-and-how-should-i-interpret-it) 2:[DaveTang's](https://github.com/davetang/learning_vcf_file) 3:[Paper](https://www.researchgate.net/publication/230658044_A_beginners_guide_to_SNP_calling_from_high-Throughput_DNA-sequencing_data)\n* bedtools 1:[Quinlan](http://quinlanlab.org/tutorials/bedtools/bedtools.html) 2:[YanhuiFan's](https://felixfan.github.io/bedtools/)\n* BWA\n* bowtie2\n* [Tuxedo Suite](http://cole-trapnell-lab.github.io/cufflinks/) 1:[YanhuiFan's](http://felixfan.github.io/tophat-cufflinks/)\n* [bedops](https://bedops.readthedocs.org/en/latest/content/usage-examples.html)\n* [picard](http://broadinstitute.github.io/picard/)\n* [jvarkit](https://github.com/lindenb/jvarkit)\n* [Exomiser](http://www.sanger.ac.uk/science/tools/exomiser) disease causing variants\n* [PopSV](https://github.com/jmonlong/PopSV) structural variants\n* [Silva](http://compbio.cs.toronto.edu/silva/) silent mutations\n* [Variant Effect Predictor](http://www.ensembl.org/info/docs/tools/vep/index.html)\n* [ANNOVAR](http://annovar.openbioinformatics.org/en/latest/)\n* [BioGPS](http://biogps.org/help/)\n* [ABySS](http://sjackman.ca/abyss-activity/)\n* [GEMINI](https://gemini.readthedocs.io/en/latest/) annotation db\n* Graphical User Interface (GUI) apps\n * [Integrative Genomics Viewer (IGV)](https://www.broadinstitute.org/software/igv/)\n * [NCBI Genome Workbench](https://www.ncbi.nlm.nih.gov/tools/gbench/)\n * [Savant](http://genomesavant.com/p/savant/index)\n * [JBrowse](http://jbrowse.org/)\n\n# Other Non-specific Tools\n* [Atom](http://atom.io/) modern text editor\n* [Reference Manager](https://en.wikipedia.org/wiki/Comparison_of_reference_management_software)\n* [Git](https://git-scm.com/) Version Control\n * [HowTo Guide](https://githowto.com/)\n * [Try Online](https://try.github.io/)\n * [Pro Book](https://progit.org/)\n * [Short Videos](https://git-scm.com/videos)\n * [Start Contributing Guide](https://about.gitlab.com/2016/06/16/fearless-contribution-a-guide-for-first-timers/)\n* [LaTeX](https://latex-project.org/intro.html)\n* [Overleaf](http://www.overleaf.com/) write collaboratively\n* [Markdown](http://daringfireball.net/projects/markdown/)\n * [Here](http://markdown-here.com/)\n* [RegEx Generator](http://www.regexr.com/)\n* [RegEx 101](https://regex101.com/)\n* [RegEx Debugger](https://www.debuggex.com/)\n* [Plotly](https://plot.ly/)\n* [Small (bioinformatic) Tools Manifesto](https://github.com/pjotrp/bioinformatics)\n* [Terminal Multiplexer](https://robots.thoughtbot.com/a-tmux-crash-course)\n* [ZSH](http://ohmyz.sh/)\n* [VIM](http://vim.rtorr.com/) o rather run 'vimtutor' :P\n* [ShellCheck your scripts](http://www.shellcheck.net/)\n* Writing\n * [Correct your Grammar](https://www.grammarly.com/)\n * [Look-up word by its meaning](http://www.onelook.com/reverse-dictionary.shtml)\n * [LanguageTool](https://languagetool.org/)\n * google translate, obviusly.\n* [Introduction to HTML](https://developer.mozilla.org/en-US/docs/Web/Guide/HTML/Introduction)\n" } ]