# BIOL398-01/S11:Class Journal Week 11

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## Instructions

### Formatting

• Sign your portion of the journal with the standard wiki signature shortcut (`~~~~`).
• Add the "BIOL398-01/S11" category to the end of the wiki page (if someone has not already done so).

### Reflection

1. What aspect of this assignment came most easily to you?
2. What aspect of this assignment was the most challenging for you?
3. What (yet) do you not understand?
4. Does "crunching" the data yourself help you to understand microarray experiments in general and the Schade paper in particular? Why or why not?

## Class Responses

### Sarah Carratt's Journal Entry

1. Manipulating functions in excel was the easiest part for me.
2. The most challenging aspect was answering the application questions and interpreting the large spreadsheet of numbers
3. I don't think there is any part of this assignment that I am not capable of understanding (the instructions were VERY clear, thank you!) but I'm just going to need time to process everything I need and really understand what I was doing with ever function and column.
4. It is really helpful to be able to do the math on my own, but it is even more valuable to have the detailed instructions beside me. I don't think I can compare the Dahlquist and Schade data very well because of the different time intervals, but it is still helpful to understand the background and how to normalize ratios and such.

Sarah Carratt 20:34, 4 April 2011 (EDT)

### Carmen E. Castaneda's Journal Entry

1. The easiest part of the assignment was applying Excel's built in formulas to do a lot of the work for me.
2. Keeping track of such a big data set was hard though. I also found it challenging trying to understand what was being asked at me at points in the assignment, the examples definitely came in handy.
3. I still don't understand what the data tells me, so like the biological significance. For instance what does the log fold change value tell me about that gene at that time period.

--Carmen E. Castaneda 00:09, 5 April 2011 (EDT)

### James C. Clements' Journal Entry

1. Converting the data into a format that MatLab could read was easiest for me.
2. The most challenging part of the assignment was figuring out what the protocol that was written for analysis in excel meant in terms of doing something in MatLab. The "cookbook recipe" for how to put the info in, cell by cell, did not tell me the overall mathematics that were going on. For example, the type of t-test being done was determined from the example lines of code, not from the directions itself.
3. I still am trying to figure out a way to make my code work for any set of microarray data with as little user input as necessary. I think this would be helpful for people who want to have MatLab crunch the data for them and not have to actually follow the protocol each and every time.
4. It helps me understand the Schade data, and it doesn't at the same time. Are the calculations that we're doing the same as what GeneSpring does? Without understanding the internal workings of how GeneSpring determines if a gene is significant, we really don't understand how experimental microarray data (such as Schade's) has been analyzed. (We do, however understand a method of analyzing the data ourselves, so we could take their data, do our own analysis and compare with other data in which we've analyzed...)

James C. Clements 00:17, 5 April 2011 (EDT)

### Nicholas A. Rohacz's Journal Entry

1. The whole excel process was probably the easiest aspect of this assignment for me.
2. The most challenging part of this assignment was thinking I had lost all my data at 11:30 pm monday night.
3. I am still trying to discover the significance of having the Pval's within certain constraints.
4. Crunching the data does not necessarily help me how the data was used to reach certain conclusions, but I do understand more about the microarray's and how exactly to normalize the data received from performing one.

Nicholas A. Rohacz 02:51, 5 April 2011 (EDT)

### Alondra Vega's Journal Entry

1. The aspect that came most easily to me was using excel and computing all the necessary data.
2. The aspect that came most challenging to me was trying to figure out why YHL030W would be chnaging its expression during cold shock. Having the data and connecting it back to biology has been hard for me. I think that I have gotten better and that I can connect more pieces, but I am not quite there yet. I am still working ion making this a strenght rather than a weakness.
3. I think that this has been one of the assignments I have understood more in comparison to others. I think this is because I understand the math behind it and what it means. I still do not understand how we are going to comapre all the data, when the Schade et al. paper has different time points than the Dahlquist data.
4. Crunching the data does help, even though I did not work on Schade's data specifically.It hepls because we see what they did and we are forced to connect back from math to biology.

Alondra Vega 01:11, 4 April 2011 (EDT)