CCB Bioinformatics Bootcamp
The Center for Computational Biology offers a 5-day condensed "Introduction to Programming for Bioinformatics" bootcamp. The goals of this course are to introduce students to Python, a simple and powerful programming language that is used for many applications, and to expose them to the practical bioinformatic utility of Python and programming in general. The course will allow students to apply programming to the problems that they face in the lab and to leave this course with a sufficiently generalized knowledge of programming (and the confidence to read the manuals) that they will be able to apply their skills to whatever projects they happen to be working on. The course assumes no programming experience, and there are no prerequisites for the course. The next "Introduction to Programming for Bioinformatics" bootcamp will be offered in June 10-14, 2019. Please follow this link to register. The schedule below shows an approximation of what is covered in the course.| Day 1: Introduction to Python | 1.1: UNIX shell and Jupyter notebooks
1.2: The Basics: Hello, World!, Variables, and Printing |
| Day 2: Functions and Control Flow | 2.1: Functions and Methods
2.2: Tests, Loops, and Escapes |
| Day 3: Data Structures | 3.1: Lists, Dictionaries, Tuples, and Sets
3.2: Fancy Data Structures: Nested Loops |
| Day 4: File Manipulations and Modules | 4.1: Reading and Writing from Files
4.2: Modules, Numpy, Scipy |
| Day 5: Using External Libraries | 5.1: Introduction to Plotting
5.2: Biopython and System Calls |
Computational Biology Core Skills Seminars
The aim of the Computational Biology Core Skills seminars is to strengthen bioinformatics training on campus by providing a setting to disseminate knowledge and experience among the student community. These peer taught seminars are organized by and for graduate students, but are open to other UC Berkeley researchers and affiliates. For Spring 2019, the core skills seminars are listed below and all seminars will be held from 12 - 1pm at 177 Stanley Hall.| March 27 2019 | Speaker: David DeTomaso
Topic: Creating Data Analysis Pipelines with Snakemake |
| April 18 2019 | Speaker: Jordi Silvestre-Ryan
Topic: Explore Deep Learning with Tensorflow |
| May 9 2019 | Speaker: Sean Wu
Topic: Combining C++ and R with Rcpp |
| Depts/Centers | Courses | Links |
| Berkeley Institute For Data Science (BIDS) | Machine learning, data science, statistics | https://bids.berkeley.edu/events |
| Berkeley Research Computing (BRC) - Research IT | Varies | http://research-it.berkeley.edu/events |
| D-Lab | Python, Excel, and more | https://dlab.berkeley.edu/training |
| R, Python | https://dlab.berkeley.edu/people/drew-hart | |
| Tutorials in R | https://github.com/dlab-berkeley | |
| Department of Statistics | R- Bootcamp | http://statistics.berkeley.edu/computing/r-bootcamp |
| Berkeley Electrical Engineering and Computer Sciences | Varies | https://eecs.berkeley.edu/academics/courses |
| Simons Institute for the Theory of Computing | Data analysis, deep learning, and more | https://simons.berkeley.edu/workshops |
| Computational Genomics Resource Laboratory | Next generation sequencing data analysis | http://qb3.berkeley.edu/cgrl/ |
| Carpentries Club | Python, R, Shell, Git, and more | https://bids.github.io/carpentries-club/who.html |
| Berkeley Center for Cosmological Physics | Varies | http://bccp.berkeley.edu/workshops/ |
| Berkeley Nanosciences and Nanoengineering Institute | Varies | https://nano.berkeley.edu/news/conferences.html |
| UCSF Bakar Computational Health Sciences Insittute | Biomedical informatics, molecular study, systems biology, systems pharmacology | http://bakarinstitute.ucsf.edu/ |
| UC Davis Bioinformatics Core Facility | Data analysis | https://bioinformatics.ucdavis.edu/ |
