Sdong - Bioinformatics Pathway

Concise overview of things learned. Break it up into Technical Area, Tools, Soft Skills

  • Technical Area: Although this past week I haven’t been able to attend any of the live meetings, I was able to grasp a general understanding of some of the functions used for data in R and Python. Additionally, I was able to learn new strategies for reading and analyzing scientific readings.
  • Tools: R programming language and Python
  • Soft Skills: I have been working on my problem solving skills since I needed to find a way on how to quickly get myself back on track with the project schedule.

Three achievement highlights

  • Understood how to properly read and analyze the scientific papers that will be used in the upcoming weeks.
  • Began connecting with others and expanding my network on LinkedIn
  • Learned and utilized programming languages to group together scientific data for analysis.

List of meetings/ training attended including social team events

  • I have been unable to attend any meetings or training due to finals and class time conflicts. However, I have been able to watch a few of the videos up until now and will be watching the other recordings in order to catch up.

Goals for the upcoming week

  • For the next week, my main goal will be to catch up and attend most, if not all, of the training and meetings. I will be re-organizing my schedule to keep me on track with my tasks. I hope to learn and practice more R and Python, and I wish to get to know my team and others this week.
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Concise overview of things learned

  • Technical Area: During this past week (and the previous week), I was able to learn a variety of new functions for processing and exporting data. Some of these include affyQCReport and limma. Using these methods, I was able to analyze the imported data and look for any outliers within the data.
  • Tools: Asana, Slack, R, GitHub
  • Soft Skills: I have been communicating with my team and keeping them up to date with my progress and whenever I need help. Additionally, I have continued to expand my LinkedIn network.

Three achievement highlights

  • I was able to create and analyze various forms of graphs that were previously unknown to me.
  • I learned a variety of libraries that I could use to help make my data easier to read in addition to highlighting different trends.
  • I have learned more about gene filtering and how to use limma.

List of meetings/training attended including social team events

  • I have not been able to attend any of the trainings due to class conflicts, but I have been able to keep up with the powerpoints and documents provided in the google drive. Apart from that, I was able to attend a Python training session in week 3 that helped me get a better understanding of the programming language.

Next week:

  • I will be leaving after July 3rd, and will be spending the next week reviewing everything I have learned during this session.

Session Assessment

  • This session was a good experience for me. I was able to learn a lot of different techniques to analyze datasets, and learned a new programming language-- R-- and Object Oriented Programming for Python. My prior knowledge of Python was limited to the basics, but the intermediate training I attended in week 3 was very useful in teaching me more. I also learned how to use affyQCReport to generate a pdf of various visualizations that can be used to pick out the outliers and see the relationships between different arrays. The most recent week, I was able to get a general understanding of the importance of gene filtering through the use of limma(). From this, I was able to learn the usefulness of the Bioconductor documentations when I need help or don’t understand how to use a certain function. Additionally, I was able to connect with a lot of people on LinkedIn and was able to learn the importance networking.
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Inactive, assessed by Lead