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If I was pursuing a career in research, would data science or computer science provide more value as a supplementary study?
#JULY20 #biomedical-science #clinical-research
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Dhairya’s Answer
Both? I assume this is context of biomedical research based on the hashtag. Many recent advances in data science and machine learning are finding their way into computational biology and biostats classes. Data science and machine learning provide a great toolkit to for doing more complex research and data analysis in the biomedical space.
Computer science can be useful too, depending on what you're doing. When I was at the Allen Institute for Brain Science, there was huge need for high performance computing and distributed systems to process high fidelity brain scans (images that were incredibly high resolution and required computing to handle pedabytes of data) and videos. Some of this need was fulfilled by hiring software engineers. But there were also phds who had multidisciplinary backgrounds as computational neuroscientists with experience developing custom high performance systems to run their experiments. Often classes like scientific computing will also cover the advanced computer science concepts you need in the context of your domain . For those classes, usually you'll need to take an intro programming class and algorithms/data structures class to get you up to speed to computation complexity needed for scientific computing.
If you can take classes in both DS and CS. If you have to choose, see what the gaps in materials offered in the biology / biomedical department and find the complimentary courses in CS , DS and stats.
Computer science can be useful too, depending on what you're doing. When I was at the Allen Institute for Brain Science, there was huge need for high performance computing and distributed systems to process high fidelity brain scans (images that were incredibly high resolution and required computing to handle pedabytes of data) and videos. Some of this need was fulfilled by hiring software engineers. But there were also phds who had multidisciplinary backgrounds as computational neuroscientists with experience developing custom high performance systems to run their experiments. Often classes like scientific computing will also cover the advanced computer science concepts you need in the context of your domain . For those classes, usually you'll need to take an intro programming class and algorithms/data structures class to get you up to speed to computation complexity needed for scientific computing.
If you can take classes in both DS and CS. If you have to choose, see what the gaps in materials offered in the biology / biomedical department and find the complimentary courses in CS , DS and stats.
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Yuezhe’s Answer
I think both of them are useful. It depends on the lab and the project. Overall, biomedical science is a very broad area and people do many things under this banner.
If you are going into bioinformatics, either DS or CS would be helpful. Some labs do tool development, and probably CS background is more useful. If you are in a lab doing mainly data analysis (e.g. RNAseq, or other genomic analysis), DS background is more helpful.
For me, I have a DS background. Now I am doing bench work. But I still use my DS skills to analyze my data and is able to generate insights that are not obvious. I also use my programming skills to develop some in-house small program to help to process data faster so that I don’t have to process all the data by hands like my other lab mates.
Overall, I will say either DS or CS skills will be helpful in the long run.
If you are going into bioinformatics, either DS or CS would be helpful. Some labs do tool development, and probably CS background is more useful. If you are in a lab doing mainly data analysis (e.g. RNAseq, or other genomic analysis), DS background is more helpful.
For me, I have a DS background. Now I am doing bench work. But I still use my DS skills to analyze my data and is able to generate insights that are not obvious. I also use my programming skills to develop some in-house small program to help to process data faster so that I don’t have to process all the data by hands like my other lab mates.
Overall, I will say either DS or CS skills will be helpful in the long run.
Updated
Jason’s Answer
Data science is probably more broadly useful since it'll force you to deal with things like statistical analysis that apply regardless of what kind of research you're doing. CS could be critical depending on what kind of research you're doing. If you're developing complex algorithms to better understand imaging, then obviously you'll need CS, but it's probably not so useful if your work involves things like collecting and analyzing samples using standard lab techniques.
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Mireille’s Answer
Generally speaking I would say yes. Great complimentary skills in so many job.