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Description: "In my internship, Biomedical Computation translated to “Bioinformatik” – the application of programming methods to help solve biological problems. In my case, the biological problems dealt with finding the genes that cause diabetes. People are doing this at the experimental level in labs; they are working directly with the mice models and the DNA and RNA.  I worked completely at the computer, using their data, as well as data that are publicly available world-wide.  My projects were initially based on previously published work. Bioinformatics-based genetics is a complex and evolving field and I had to start somewhere.  In the beginning, I tried replicating papers in order to familiarize myself with the programs and languages used in the field (I coded mainly in PERL and R, sometimes in C).  Later I tried adjusting or combining methods to fit the lab data. My work was more informatics-based than biology-based and also involved heavy use of algorithms and statistical tests (several of which I never knew before).  The ability to perform research online also came in handy.  Throughout the internship, I was often confronted with common problems facing everyone in Bioinformatics – different data types, version control, and translating information between biologists and people in informatics.  I don’t think that placement in this field would necessarily result in the same projects that I had – I had significant input as to what I wanted to pursue.  In the future, I think biology students, without any knowledge of computer science (or vice versa), could find projects of interest at DIFE and MicroDiscovery."

Comments: "The most interesting and rewarding part of my internship was the amount of input I had.  In previous internships, I have always been just an assistant to a professor or PhD student, doing whatever work they didn’t want to or have time to do.  Here, I was given full control over my projects.  If I found a paper with a different method from what my supervisor’s proposed, they allowed me to explore it.  If I didn’t agree with their ideas, they listened to mine and often allowed me to try them. I have gained insight into something unique about my field – no one knows what is right.  In genetics and bioinformatics, there is no right answer.  In classes at Stanford, we learn so much about theory and methods that have always been established.  My internship gave me the opportunity to put things into practice and use what I know to propose my own methods.  It was extremely rewarding in the end to be able to calculate and present results that were truly my own."

German language skills:"My German language skills have improved significantly, but not as much as I had hoped.  In the Sciences, students are required to learn English – important resources are in English, the best journals only print in English, and PhD students must give presentations in English.  Many students in the lab saw me as an excellent way to practice their English.  Also, I often had trouble explaining biological and statistical questions in German.  Although most computer programs were in German, that didn’t really help me in terms of conversational skills. What helped me the most were the lunchtime conversations and interactions with Germans outside of the internship (z.B. playing with a Fußball team)."

For further information, please write to: ngonz@stanford.edu