Summer 2019: Difference between revisions
Jump to navigation
Jump to search
imported>Weigang |
imported>Weigang mNo edit summary |
||
Line 5: | Line 5: | ||
# No use of phone or laptop during lab meetings | # No use of phone or laptop during lab meetings | ||
=Schedule= | =Schedule= | ||
* June 19 (Wed). Summer research kickoff. Papers assigned. | * June 19 (Wed). Summer research kickoff. Papers assigned. To prepare for Python tutorial, install the jupyter notebook in one of two following ways (by Edgar): | ||
** Installing the Anaconda Distribution (https://www.anaconda.com/distribution/#download-section): This is the easiest way to install Python on your machine. It also comes with a lot of packages for data science. However, it is quite heavy (~3GB), so if space is an issue you can try installing Miniconda. If you choose to install Anaconda, you don't need to install any additional packages since they are going to be installed automatically. Make sure you download Python 3. | |||
** Installing Miniconda3 (https://docs.conda.io/en/latest/miniconda.html): This is like a mini version of Anaconda that comes with the Conda package manager and Python. It doesn't include any packages so it requires less space. | |||
*** Installing on MacOs: https://docs.conda.io/projects/conda/en/latest/user-guide/install/macos.html | |||
*** Installing on Windows: https://docs.conda.io/projects/conda/en/latest/user-guide/install/windows.html | |||
*** Once you install Miniconda, you can use the conda command on your terminal to install other packages: | |||
<syntaxhighlight lang='bash'> | |||
conda install numpy | |||
conda install pandas | |||
conda install matplotlib | |||
conda install jupyter | |||
</syntaxhighlight> | |||
* June 21 (Fri). Python Tutorial I. Jupyter notebook, string, list, conditions, loops (by Edgar) | * June 21 (Fri). Python Tutorial I. Jupyter notebook, string, list, conditions, loops (by Edgar) | ||
* June 24 (Mon). Python Tutorial II. string functions, function, dictionary, modules (by Edgar) | * June 24 (Mon). Python Tutorial II. string functions, function, dictionary, modules (by Edgar) |
Revision as of 12:33, 27 June 2019
Rules of Conduct
- No eating, drinking, or loud talking in the lab. Socialize in the lobby only.
- Be respectful to each other, regardless of level of study
- Be on time & responsible. Communicate in advance with the PI if late or absent
- No use of phone or laptop during lab meetings
Schedule
- June 19 (Wed). Summer research kickoff. Papers assigned. To prepare for Python tutorial, install the jupyter notebook in one of two following ways (by Edgar):
- Installing the Anaconda Distribution (https://www.anaconda.com/distribution/#download-section): This is the easiest way to install Python on your machine. It also comes with a lot of packages for data science. However, it is quite heavy (~3GB), so if space is an issue you can try installing Miniconda. If you choose to install Anaconda, you don't need to install any additional packages since they are going to be installed automatically. Make sure you download Python 3.
- Installing Miniconda3 (https://docs.conda.io/en/latest/miniconda.html): This is like a mini version of Anaconda that comes with the Conda package manager and Python. It doesn't include any packages so it requires less space.
- Installing on MacOs: https://docs.conda.io/projects/conda/en/latest/user-guide/install/macos.html
- Installing on Windows: https://docs.conda.io/projects/conda/en/latest/user-guide/install/windows.html
- Once you install Miniconda, you can use the conda command on your terminal to install other packages:
conda install numpy
conda install pandas
conda install matplotlib
conda install jupyter
- June 21 (Fri). Python Tutorial I. Jupyter notebook, string, list, conditions, loops (by Edgar)
- June 24 (Mon). Python Tutorial II. string functions, function, dictionary, modules (by Edgar)
- June 26 (Wed). Python Tutorial III. BioPython (Edgar & Muhammud)
- June 27 (Thur). Paper presentations
Participants
- Dr Oliver Attie, Research Associate
- Brian Sulkow, Research Associate
- Saymon Akther, CUNY Graduate Center, EEB Program
- Lily Li, CUNY Graduate Center, EEB Program
- Christopher Panlasigui, Hunter Biology
- Summer Interns: Muhammad, Radhika Mohan, Oscar Eng, Oliver Cai
Journal Club
- A Python Tutorial (by Edgar)
- a Unix & Perl tutorial
- A short introduction to molecular phylogenetics: http://www.ncbi.nlm.nih.gov/pubmed/12801728
- A review on Borrelia genomics: https://www.ncbi.nlm.nih.gov/pubmed/24704760
- A model of immune selection: He et al (2018). https://www.nature.com/articles/s41467-018-04219-3
- A model of flu evolution: Neher et al (2016). https://www.pnas.org/content/113/12/E1701?ijkey=72c6025e999dd043d32f6822dc06c7356d8494b2&keytype2=tf_ipsecsha
Projects
Borrelia genome evolution (Saymon)
- genome tree & phylogeography
- genome intragression
Antigen evolution
- Borrelia OspC
- Immune selection model
- Flue