I know most people who read this might have some idea of what it is I do, and some people have absolutely no clue. First off, I am a graduate student working towards my Ph.D. in chemistry. The research I do is applied data analysis (chemometrics) of Microarray data. Now the question becomes, what kind of data analysis, and what the heck are microarrays?
There are many situations in chemistry and biology where a few individual components interacting with each other can give rise to very complex outputs. Unfortunately, very often we are only able to measure the complex outputs (UV vis spectra of mixture), when what we are interested in measuring are the individual components that make up the mixture. This happens especially in chemistry, where chemical concentrations of 3 components may change over time, and the spectrum we can measure of the mixture is very very complicated. My supervisor developed a method that is able to pull out the primary components that give rise to the complex picture we are able to measure, telling us a lot of information about the actual system we are looking at. If you want to know more about the kind of research our group does, check out our website.
All proteins in the body come from DNA. There is a flow of information from DNA - RNA - Protein. Knowing how much protein is being made at a particular moment in the cell and under what conditions can tell us a lot about how the cell responds to its environment, as well as what genes may be responsible for causing a disease, like cancer for example. We can measure the amount of RNA, and therefore the rough amount of protein being made in the cell using DNA microarrays (really good movie here).
It get's especially interesting when measuring gene expression over time, as the amount of data that results becomes enormous, and deciphering which genes are responsible for the majority of the changes becomes very difficult (7000 genes, 20 timepoints, = 140000 data points). This is where I come in. We use the techniques that were developed for chemical timecourse data analysis, and apply them to DNA microarray data in order to find out the most important contributors to the changes in gene expression.
Why would we do this? Mainly because it seems that most of the methods currently used to analyze microarray data either don't have a valid biological interpretation, or they work too much to classify every gene into a particular box, which is virtually impossible in a biological system, as gene expression can have a lot of overlap, and yet be different. Where to draw the line in classifying (clustering) is open to interpretation.
So, I am working on validating the method using various microarray data sets, and providing biological interpretation to the results (do the results we get from the method make sense with other information we know from other biological studies of the organism?), as well as working to integrate the data analysis with other biological knowledge to help make it easier to make conclusions from the data we have.
If none of this makes sense, don't worry, I spent a year doing work here before I truly began to understand what it was I was doing. In a nutshell, I use statistical methods to analyse very complex biological data that tells us about gene expression in an organism. This can be used to help us understand a lot about the basic biology of an organism, as well as diagnose the causes of some diseases.
I hope this helps answer the question of what I do for a living. Oh by the way, I don't do any of the actual creating microarrays, or extracting the RNA, I just get the images and do the data analysis. So yes, I'm technically getting a degree in chemistry, but the only time I handle chemicals is when I teach in the undergraduate labs. Other than that, I spend my days in front of a computer, doing analysis (hence analytical chemistry).
Links to more information:
DNA, RNA, protein, chemometrics, DNA microarrays (1, 2), my research group.
General_, Science / Tech News_
There are many situations in chemistry and biology where a few individual components interacting with each other can give rise to very complex outputs. Unfortunately, very often we are only able to measure the complex outputs (UV vis spectra of mixture), when what we are interested in measuring are the individual components that make up the mixture. This happens especially in chemistry, where chemical concentrations of 3 components may change over time, and the spectrum we can measure of the mixture is very very complicated. My supervisor developed a method that is able to pull out the primary components that give rise to the complex picture we are able to measure, telling us a lot of information about the actual system we are looking at. If you want to know more about the kind of research our group does, check out our website.
All proteins in the body come from DNA. There is a flow of information from DNA - RNA - Protein. Knowing how much protein is being made at a particular moment in the cell and under what conditions can tell us a lot about how the cell responds to its environment, as well as what genes may be responsible for causing a disease, like cancer for example. We can measure the amount of RNA, and therefore the rough amount of protein being made in the cell using DNA microarrays (really good movie here).
It get's especially interesting when measuring gene expression over time, as the amount of data that results becomes enormous, and deciphering which genes are responsible for the majority of the changes becomes very difficult (7000 genes, 20 timepoints, = 140000 data points). This is where I come in. We use the techniques that were developed for chemical timecourse data analysis, and apply them to DNA microarray data in order to find out the most important contributors to the changes in gene expression.
Why would we do this? Mainly because it seems that most of the methods currently used to analyze microarray data either don't have a valid biological interpretation, or they work too much to classify every gene into a particular box, which is virtually impossible in a biological system, as gene expression can have a lot of overlap, and yet be different. Where to draw the line in classifying (clustering) is open to interpretation.
So, I am working on validating the method using various microarray data sets, and providing biological interpretation to the results (do the results we get from the method make sense with other information we know from other biological studies of the organism?), as well as working to integrate the data analysis with other biological knowledge to help make it easier to make conclusions from the data we have.
If none of this makes sense, don't worry, I spent a year doing work here before I truly began to understand what it was I was doing. In a nutshell, I use statistical methods to analyse very complex biological data that tells us about gene expression in an organism. This can be used to help us understand a lot about the basic biology of an organism, as well as diagnose the causes of some diseases.
I hope this helps answer the question of what I do for a living. Oh by the way, I don't do any of the actual creating microarrays, or extracting the RNA, I just get the images and do the data analysis. So yes, I'm technically getting a degree in chemistry, but the only time I handle chemicals is when I teach in the undergraduate labs. Other than that, I spend my days in front of a computer, doing analysis (hence analytical chemistry).
Links to more information:
DNA, RNA, protein, chemometrics, DNA microarrays (1, 2), my research group.
2 comments:
I think it's important you express your views, because there are a lot of people who find it difficult to reconcile Christianity with science at the moment. I'd be intrigued in knowing your thoughts on Calvinist doctrine, hell and all those tricky things, but I suppose these things require a lot of space.
Wow, thanks kieran. I'm glad to see that someone actually reads this place besides me. A lot of people do have difficulty reconciling the two, I had a very interesting conversation just last night with a young lad who is having that very problem.
To answer your questions in a comment:
Calvinist doctrine - havent had a chance to read much on that, still trying to get my first full reading of the bible done.
Hell - well, from what I understand, hell is where those who chose not to see the evidence for God and rejected him will be, completely cut off from the love of Christ. To me that sounds much like what life is for an Atheist now, except they don't know what they are missing. So from my reading and discussions with others, it will be the same, except those in hell will realize what they are missing, and that is what will truly torment them.
And already this is a long comment. So easy to write too much. Yeah, much of this would take up a lot of space, but I would like to write about it, I just need to find ways to break it up.
Thanks for stopping by.
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