Apr 292015
 

Happened to see this article about Neal Copeland and Nancy Jenkins. Fascinating experiences!

I love their idea about selecting postdocs through the “lunch test”, and on postdocs with “50% success rate” to those “luck happens with hard work”. I should follow their advices when selecting students and postdocs in the future… It is a fun read. I only feel a little sad that they decided not to have kids. We are lucky that academic environment nowadays are much more friendly to female scientists with family. Also, there are enough successful female scientists now to form a support network.

Thinking again about this “lunch test”, you need to be smart, fun, and nice to do well here. I am reminded of my colleagues like Myles Brown, Soumya Raychaudhuri, Zhiping Weng, and Yu Xue. I am not so good in conference or consortium meeting meals. Some of the difficulty is due to race, gender, and confidence. In addition, I should have more fun in life, not necessarily in the form of having lots of fun activities like travel or sports, but genuine peace and joy in the heart. This would mean that we work hard only on the things we enjoy and drop the balls in some “academic niceties”. Hmm…

Apr 282015
 

Very often a computational genomics project in the lab requires the output of some tables. I noticed in many cases, some number columns have numbers that stretch VERY LOOOOOOONG. To display a chromosome location, it is totally legitimate to use a long number, e.g. chr1 42392716, because it is different from chr1 42392715 and chr1 42392717. However, in some other calculations, such as false discovery rate, transcription factor motif matching score, differential expression fold-change, it would not make sense to have 10 significant digits. For FDR, most people just want to know whether the gene / peak is around 1%, 5%, 20% or 80% FDR, so there is no need to show FDR as 1.238346226253182% (our FDR estimate simply doesn’t have that level of accuracy). Sometimes from cross validation, we know that the area under the curve of our prediction is around 0.813 (pretty good), then it would make sense to only use 2-3 significant digits to make classification predictions, even though the regression model might give 100 digits after the decimal points. Using fewer significant digits is often easier to visualize, creates smaller-sized files, and makes better sense.

Apr 042015
 

I have a long commute everyday. In order to stay awake during driving, I buy 2 audiobooks from Audible every month, and listen to them on my iPhone on my drive. Over the years, the books I enjoyed most are biographies, including the biographies of people (Tina Fey, Frederic Chopin, Louis Zamperini, etc), the biographies of cancer (Emperor of All Maladies) and economics (The Making of Modern Economics), etc. Having read the biographies of Alexander Hamilton and George Washington, it is hard for me to like Thomas Jefferson. However, having promised my husband to read the biography of Thomas Jefferson, I recently finished it to see his side of the story. Jefferson is a very complex and interesting character, with his wisdom and pragmatism, and his weaknesses (financial and slavery). What really intrigued me was how he recover from setbacks in life. As the war time governor of Virginia, Jefferson didn’t sufficiently prepare the state for the British invasion, and fled the state capital as the British arrived. His political career seemed finished in 1781. The next year, he lost his beloved wife of 10 years, and his life seemed finished. However, through the support of his family and friends, reading and science, horse riding and letter writing, change of environment, he gradually recovered his reputation and confidence, and achieve so much more later in life.

Being a scientist, it is natural that our scientific explorations experience ups and downs, and our careers ebb and flow. What I found to be very important is when things go well and opportunity strikes, we work like hell to move ahead. But even more important is that when things don’t go well and we are struggling to find a way out, we have the ability to lay low with grace. Just hang in there, make small steps forward, even stepping on the same spot or sliding a bit to shift some focus, but don’t drop the ball (掉链子) and totally loose grounds. What do I mean by “things not working well”? E.g. a course project got a bad score despite us working on it for over 30 hours, our teaching got a bad review, our experimental finding turned out to arise from an artifact, our paper got rejected or scooped, our grant didn’t get funded or renewed, an illness, a divorce, the loss of a loved one. What do I mean by “drop the ball”? E.g. too stressed out to even turn in the last project and going to the final exam thus earning a D in a course thus loosing PhD candidacy (turning in whatever you have done and taking the final exam with the best of your efforts could have earned a B- and save the degree), quitting science when one technology you are an expert on was overtaken by a newer technology (I considered quitting when finding myself working on the “dead technology” of ChIP-chip after my second maternity leave when next generation sequencing arrived), no show on progress meetings, lab meetings or in the lab completely when projects seem to be at a dead end, crying and blaming advisors for giving them the wrong project or not spending enough time on their project when paper got rejected, blaming lab members and collaborators under financial or publication pressure, disappearing from the lab for days or weeks, sabotaging lab members experiments or poisoning lab members (OMG!), etc. What sets people apart is not how much progress one makes in smooth times, but how resilient s/he is during setback. The ability to just hang in there, the ability to do the minimum at least to get by even when you are numb or hurt, the ability to lay low with grace, they will carry people in the long run.

What if you did drop the ball? Maybe we all did at different degrees occasionally, as long as it is not criminal offense. Don’t worry, time is a great healer. Didn’t Jefferson recovered from his governor fiasco? Just get back on your feet, and try again!