Skip to main content

Jimmy Kim Week 3-4

Week 3 and Week 4


After somewhat settling down in the new lab, the first couple of days were more of getting the finishing touches on the new lab. I helped the graduate students to get all the machines working such as the laser. After doing mostly basic stuff for the first two weeks, I actually started to work on my project for the summer, which is the program a machine that connects the laser and the laser platform, which moves around, to collect data from the samples. Through week 3 and week 4, I mostly went in and out on this project. I did a lot of coding, but I also helped other graduate students with their own projects. For instance, I helped Anu, a graduate student in my lab, collecting graphs and peaks of samples using spectroscopy. While doing this, we had to use liquid nitrogen in the process. Therefore, we played around with liquid nitrogen. I also helped other graduate students collecting data. We also had a lot of fun. Since I am a really big soccer fan and I have been watching a lot of the World Cup, we watched some games in the lab together as well because some people in the lab also likes soccer. I am having an experience that is not only a learning experience but also a very fun experience.

Comments

Popular posts from this blog

Kylie Heering, Week 2 at the Goldstein Lab

We started off our week with a congratulatory acai bowl trip to celebrate Preston’s acceptance into a training grant program. Acai bowls in California top Playa Bowls (no question about it). From what I can tell, its a pretty huge honor to be recognized by this grant, but he’s really humble about it. On Monday, Preston and I decided that testing antibodies that have never been tested on prostate epithelial cells before would be a good objective for my first Western blot on my own. We needed to probe for ASCT2, a glutamine transporter, and GLS in order to determine if their corresponding antibodies are functional. Antibodies are crucial for Western blots because they bind to the protein of interest (POI), allowing for us to qualify its expression after imaging. As such, Preston wanted to make sure they worked by probing for ASCT2 and GLS on three different cell lines. Cell lines are commercially purchased human cells that have been immortalized (modified to grow indefinitely) by telome...

Alan - First Week at UCSF

Hi Everyone! After arriving in San Francisco last Sunday, I spent this past week settling into the downtown Berkeley apartment that I’ll be sharing with Rohit for the next couple of months, as well as learning my way around the Roy lab at UCSF. First day at the lab was really exciting. Here are a couple pictures of the Mission Bay campus, which was completed just a few years ago. Everything is super new and modern, and there’s still construction for other buildings going on around the campus. Most of the people who work at the Mission Bay campus are either professional researchers or doctors/nurses for the nearby hospital. The graduate students take most of their classes at the original Parnassus campus (where Maya is). I work in Byers Hall, which is connected to Genentech Hall and a short walk down the block from the shuttle stop. There are three other volunteers working for the Roy lab this summer – Kimmai, David, and Pujita, who are all undergrad college students...

Jaewon Oh - Week 7 and 8

Finally done here with my experience and I wish I had more time keep researching so that I have something a little more "finalised" to present. But I guess that's what past EXP kids meant when they said that 8 weeks of research is not enough and I'll have to work with what I've got. To solve the problem of not having enough data points, we used the online TCGA database for raw data that would be used to calculate mutation rates. Mutation rates were calculated through an R coding script that Dr. Cannataro had made. Because the mutation rates were tumor specific, we had to change the proportions that were obtained from the IARC database using data from another database called cBioPortal. Basically we had to multiply the number of times a certain variant was seen in the IARC database by the percentage of tumors that have a tp53 mutation, because our mutation rates are calculated across all tumors in specific cancers (confusing, I know). After graphing the mutatio...