For week 6 we did a flash gel. The results are at the top. I will also be helping Chad and Stacey with their project and learning about bioinformatics. The picture just above shows the genes for different species of deinococcus.
This is a tough question for me, because lately I've been jumping around between career ideas. My major is Applied Computing with a concentration in cybersecurity. I would like to work in cybersecurity, but with Applied Computing being so broad, I'll be qualified for all kinds of computing paths such as machine learning, software engineering, and (as I recently found out from a job ad) even some bioinformatics positions. I have the most interest in machine learning, bioinformatics, and cybersecurity. If I'm being honest, I don't necessarily have the have the cybersecurity concentration because I for sure want to go into cyber security. I just want to give myself more options since the cybersecurity field is extremely desperate for workers right now. If I end up with a job in cybersecurity after school, then that's great. And if not, I'm also ok with that. A company that I would specifically like to work for one day is Microsoft, however, I couldn't say wh...
Hello! This week I read Chapter 4 in Data Visualization of R by Rob Kabacoff. Last week I read Chapter 3 on univariate graphs, which plot data about a single variable. Chapter 4 is about bivariate graph, which are used to show the relationship between 2 variables. The type of graph used depends on whether the variables are categorical or quantitative. Categorical vs. Categorical Much like a univariate graph, a bivariate graph typically uses various types of bar charts to display categorical data. There are 3 different types of bar charts used, and I'll display pictures of them all. This time, I am not going to go into detail about modifications such as color, size, etc. because it is the same as for univariate graphs. The data set used displays the relationship between automobile class and drive type: 4 wheel drive, front-wheel drive, and rear-wheel drive. Stacked bar chart The stacked bar chart is the default bar chart in R, so there are no special commands to use thi...
Yay! The district's computer system is back up, so I can access the blog from my computer again. This week I read about and practiced Univariate Graphs. This variable can be categorical or quantitative. A categorical variable is something such as race or sex, is usually plotted using a bar graph, pie graph, or tree map. A quantitative variable is something like age or height, and is usually plotted using a histogram, kernel density plot or dot plot. Both categorical and quantitative variables use the ggplot2 function, which I used last week. I followed along with the book, and started out by following the examples to demonstrate a categorical variable. The dataset being used is The Marriage dataset that has the records of 98 couples in Mobile County, Alabama. Categorical Variable Graphs Bar Graph The first graph demonstrated is a bar graph. Just like with the graph from my last blog, you can change and edit everything about the graph including color, using percent symbols fo...
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