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2018: Year in review

Research careers often entail relatively few concrete achievements over relatively long periods of time. Even when something good happens, it feels like rejection is right around the corner. To cheer up during the long stretches of waiting and the many rejections, I decided at the beginning of 2018 to keep a running list of achievements. I wanted to include products that weren’t necessarily full-fledged papers, including blog posts, talk acceptances, big grant submissions (not just acceptances, since those are way rare!) This year did end up being really good in terms of paper acceptances and I think that some of the smaller things allowed me to gain the extra confidence and ability to drive home some bigger things. Here is my list:

  • I had a tweet/blog post on regression that kind of went viral Where viral = viral for me. I was really happy about this, since these were thoughts that were swirling in my head since grad school and it was nice to get them out and also get a bit of validation by hearing how others found it useful (January 10)
  • I joined the “deep review” project (collaboratively written paper reviewing deep learning in biomedical research). I don’t work in deep learning per se, but I like to think a lot about how different methods should be applied and what their caveats are. It was an awesome learning experience being on this kind of modern collaborative project and I’m really indebted to the New PI Slack (NPIS) group. I had read a preprinted version of the paper and had a comment on an example that considered Duchenne muscular dystrophy, a disease that I have worked on before. I asked Casey Greene about it and he encouraged me to go ahead and make the edits on GitHub. I ended up contributing enough to the new version to be listed as an author. (January 19)
  • My commentary comparing biocuration to systematic reviews was accepted in JCO PO. I felt good about this since this was again something that I had been thinking about for a while now so I decided at some point last year to just put my thoughts on paper. I had some general ideas so came up with a short draft, then recruited some other super knowledgeable folks to flesh out the details. This is the first time this kind of project has come together for me. (January 19)
  • By the end of February, I already had 4 papers accepted (the “deep review,” the commentary paper, 2 other collaborative papers.)
  • I gave a talk a Brown University, invited by my friend, former NCI postdoc colleague, and coauthor Orestis Panagiotou. (April 10)
  • Another paper was accepted by JCO PO that I was a co-author on, considering an eye-tracking study for usability of molecular diagnostic reports. I was involved in the original study design and grant submission for it and it was led by a former ICBI postdoc, Vishakha Sharma. It was also a really important project for the center and I was very happy to see it completed. (May 4)
  • The supplement to my R21 grant was officially awarded! My R21 is funded through the NCI Informatics Technology for Cancer Research (ITCR) program and the supplement is for a collaboration with a group funded through the Innovative Molecular Analysis Technologies (IMAT) program. I had applied for it last year so kind of wondered whether it was “fair” to list it as an accomplishment for the year. Then I decided that I might as well. (May 21)
  • I submitted an application for an NIGMS R35 “MIRA” grant. This was my biggest application to date as a PI! I am again indebted to NPIS for finding out about this! It’s a grant that is meant to fund early stage investigators’ NIGMS-related research programs, as opposed to individual projects, which made it easier to write (for me at least!) than a regular project-driven grant. The chances of acceptance are always low for any individual grant, but I felt good just knowing that I could apply for this kind of big thing. If it doesn’t get funded, I will apply for sure next year as well! (September 28)
  • By mid-October, I had 6 papers accepted (the ones mentioned above plus one more collaborative paper.)
  • I got a talk accepted at the CSHL Biological Data Science meeting (slides here). (October 10)
  • My paper with my former PhD adviser Jeff Leek on estimating the false-discovery rate (FDR) conditional on covariates was finally accepted by PeerJ. More on this paper below. For now - let me just say this was a very long process and it was such a relief to have it officially out. (October 24)
  • I also got a talk accepted at the AMIA 2019 Informatics Summit. (October 30)
  • I was also invited to give talks next year to the Breast Oncology Program at UCSF and the Bioconductor conference, which will be in New York. (November)
  • I posted a preprint for metabolic biomarkers in a mouse model of Duchenne muscular dystrophy, which I’m a co-first author on. (November 23)
  • I read 8 books! Hoping to finish one more before the end of the year. They included books about science, like The Emperor of All Maladies, She Had her Mother’s Laugh and The Immortal Life of Henrietta Lacks, and books about time management and people management, like Deep Work and 168 Hours.

As I said before, this has been a really good year! However, most of the projects that were completed were things that I had started a long time ago. The FDR paper, for example, originated in an idea that Jeff had, based on some of my PhD work, that he wrote a blog post on June 13, 2013. Just for perspective, since that time, I switched from being a postdoc at NCI to being faculty at ICBI, I had a second child, and Simona Halep won the French Open (she reached her first Grand Slam final in 2014 and played two others before winning in 2018, all during the time it took for this paper to be completed). Of course, the work took a fair amount of time to complete, but a substantial amount of time was also spent looking for a good home for the paper. In fact, we first posted a preprint of what’s now a super outdated version of that project on December 30, 2015. The great thing about posting it as a preprint was that it did get read a fair bit and even included in a comparison of methods for FDR control, in which it was shown to have a good performance.

Some other things felt very satisfying because they were the result of seeds I had planted a while ago. For example, I had wanted to do more work in Duchenne muscular dystrophy, since my 2016 work on metabolic biomarkers for this disorder. I kept asking collaborators about it until the right project came along. I wanted to be able to present more at conferences/seminars and get both more talks when submitting abstracts and (any?) invited talks. I whined about this for a while, then actually started taking some actions to improve the situation. For example, I asked around about what the most appropriate conferences would be and put myself out there more, both by talking to friends and colleagues (including Subha Madhavan, our center director, as well as NPIS), and by being more aggressive about self-advertising on Twitter.

That being said… If you notice, there was still that seemingly “empty” time between May and September when apparently nothing got done. I felt it acutely at the time too. I mean, I was definitely working (as well as taking some family trips!) and hopefully planting seeds for some good things that will happen 2019-2023. I also got some reading done during that time: I feel really good about the 8 books I’ve read; the number is surely low compared to many, but I’ve gone through years of not being able to complete any books, so getting back on track feels very nice. In 2019 I want to be somewhat more deliberate about planting seeds during these “empty periods” but also try to worry a bit less about them.