Aug 282015
 

Developing scientific reputation relies on publishing impactful discoveries, developing widely used algorithms, but probably equally importantly delivering insightful scientific talks. In some conferences, I am often chagrined or amused by talks in the following styles (sometimes a talk could combine the 3 styles which is quite a sight to behold :):

A speaker goes over all the major publications (Nature, Science, New England JM, Lancet, you name it) to demonstrate that a new direction (often following a US or EU initiative) is important, although none were their own study. It is like a 科普 journal club which treats the other scientists in the audiences like school children. Actually such talks are often good for student audiences who may not be as well informed about the new trend, so are quite informative and inspiring. Also such talks often signal that the government will be spending major $ on this new direction, so we should start to scheme and get a slice of the pie :).

A speaker says “the computational method is very complicated, so I won’t go into the details, but trust me, here is our finding”. Then a list of biological observations is given, and the speaker says “we don’t know what this means” or “I don’t really understand the biology”. It is possible that these methods are good and the discoveries are true. However, for these results to be taking seriously, the data / method need to be explained to earn credibility, computational biologists should learn the domain biology and talk more professionally about the biological findings.

A speaker says, “the method is very simple la! so I won’t go over the details, but we have boat loads of money to generate tons of data, and we integrated everything, so here is our results”. Then to the abhorrence of the audiences, the “results” presented are “we filed a patent or developed a kit”, “we obtained some major government awards or venture capital funding”, “this method can really be used to solve all biomedical questions, which can be demonstrated by the following 100 published papers from our group”, or “we found a new use of an old drug or a new drug combination, some have clinical trials ongoing, but for intellectual property reasons I can’t tell you what it is”. Such talks are often super effective ;), since naive audiences often fall head over heels to join the speaker’s lab.

A good scientific talk should focus on one coherent biological study, start from the motivation, explain what data is used, how the computational method works (at least the key intuition), then present specific biological findings with thoughtful biological interpretations and full appreciation of potential limitations. If the talk is a computational method, then explain why and how it is developed, what the main functional features and advantages are, where the method can be downloaded for use. The audiences could learn how a study progresses from a logical flow, how to a use tool / website / database to speed up their analysis and hypothesis generation, how to use the thinking of the presented method to develop their own methods, how to use the presented biological findings to inform their next experiments. It is OK to present published studies, but probably even better studies under preparation, review, or revision (many reputable international conferences encourage speakers to present unpublished work).

I hope that with more and more great scientists getting into computational biology, the field becomes more mature, our scientists could learn to deliver professional, more informative and insightful scientific talks in scientific conferences. At least I hope speakers at the Young Bioinformatics PI Workshop try their best to give good talks. Only when we can do so can computational biologists be respected by experimental biologists, can Chinese scientists earn international reputation.

P.S. Recently Xiaowei Zhuang gave a talk at our CFCE retreat. She talked about many different studies and papers from her group, but was super clear on the intuition as well as the significance behind each study. You could see how their technology progresses over time, and could really learn a lot which was very exciting. I guess it is possible to cover many topics in one talk and still do a great job, but Xiaowei’s scientific expertise as well as her talk style (which I am sure take a lot of hard work to hone) is quite a different league!

Aug 182015
 

Recently I finished The Wright Brothers book. One sentence struck me: The best dividends on the labor invested have invariably come from seeking more knowledge rather than more power. Science will be a better place if scientists can all follow this… The brothers were stoic, diligent, resilient, and detail oriented. Reading the book not only inspired me about future research, but also brought back some sweet memories of our past research. There were a few times in my life when we were learning a lot and making good progress in research, such as the time we were developing MDscan, understanding epigenetics from analyzing the data Keiji Zhao (Barski et al Cell 2007), and recently learning about CRISPR screens. Despite the setbacks, the excitement from new knowledge or good results kept us going. The book was heart warming, and gave me the confidence that with careful and hard work, everything is possible.

However, a few days after I read the Wright Brothers book, I read about Howard Armstrong (Dreamers and Deceivers). Very few people heard about Armstrong, but he made seminal inventions, most notably regenerative circuits for radio amplifiers and FM radio transmission. However, Armstrong lost the patent lawsuit of the first to Lee Forest (under the backing of AT&T), then the FM patent lawsuit to RCA. Even though experts completely credited Armstrong with these inventions, his patent losses caused both financial and emotional exhaustion, and Armstrong committed suicide. It was a very sad story, and I almost want to give up on science.

After reading the two stories, I thought about why the inventions between Wright brothers and Armstrong came to so different outcomes. Here are three reasons I came up with:

1. The Wright brothers had each other for support, whereas Armstrong worked kind of alone. In science, we need enough colleagues who are our close friends for support us in science, career development, and occasionally in personal life.

2. The Wright brothers understood the power of public relationship, and knew how to time their flights in order to generate enough public Wow! Armstrong was going against the PR machine of AT&T and RCA so lost his cases. In science, institutional PR department could certainly help, but for us well prepared papers and talks are our most effective PR.

3. The Wright brothers grew up in a cultured environment, and their father was a bishop. Despite their simple life, the brothers have refined taste and wide knowledge, what Hart Berg called “capital Exhibit A”, which inspires confidence. I sometimes marvel at my colleagues’ talents and knowledge outside science, such as art (Nelly Polyak), music (David Fisher), literature (Judy Garber), and social (Myles Brown) matters.

So scientific genius and hard work are necessary, but without the other important components, we could end up a sad story like Armstrong.