The other day, after reading a book on copyrighting by Joe Sugarman, I decided to use one technique that he suggests for coming up with a title for an upcoming talk.
The technique is simple: brainstorm. Don’t just write one title. Write 25 or more. Then pick the best one.
So I started brainstorming. I wrote some titles. I wrote some more. I started feeling silly, but I forced myself to write some more.
Towards the end, I got a little loopy. You can see the whole list below.
I then went back and rated them all, 1 (best), 2 (ok) or 3 (bad). I sorted them all in a spreadsheet, and removed the 2’s and 3’s.
I had about 5 left.
One kept beckoning to me. I just could not bring myself to delete it, or pick one of the others above it.
Guess which one?
“Modeling biology with equations is like strapping a V8-engine to a horse drawn buggy”
If I had written this title in my standard way, the most likely outcome would have been:
“Multi scale systems biology modeling with computer agents”
Which one sounds more interesting? I find the former far more compelling, due to the strong visual.
And, it conveys an important subtext that the second, more “safe” title doesn’t – that our tools aren’t necessarily right for the job.
Who knows how the folks at the receiving institution will like it, but it gave people around here a good laugh. They liked the title. I wrote the abstract in a more serious tone – but it did address the point made by the title.
This is an example of “Marketing Your Science” in action. A boring title is less likely to catch someone’s attention. If it doesn’t catch their attention, then they’re unlikely to come to the talk. If they don’t come to the talk, then what is the point of giving it?
Here is the list of possibilities I brainstormed (I’d like to see your vote in the comments for which one you prefer):
Agents are everything
Agents and fractals
Agents and fractals: modeling self similar protein behavior
Modeling self similar protein behavior
Multi scale systems biology modeling with computer agents
Protein behavior as a fractal mirror to nature
How complexity arises from simplicity in biology
Cells are simple, but our models that are complex
Proteins are simple, but our models are complex
Of birds and proteins: how modeling reveals fractal self-similarity
Birds are made of proteins and birds are like proteins
The Birds, the bees, and the proteins: how nature mirrors itself at multiple scales
Taking cues from the birds and the bees to construct realistic cellular models
Can cancer be solved by specialists? Or does it require a generalist.
It’s not the size of your CPU, it’s how you use it
It’s not the size of your equation, it’s how you use it
From equations to agents – boiling the complex down to the simple
Models as tools – it’s all how you use them
Modeling biology with equations is like strapping a V8-engine to a horse drawn buggy
“You have lots of power but won’t get very far”.
Representations of proteins: equations or agents?
From the simple arises the complex: can we mirror this in a computer?
Biological complexity arises from simplicity – can we model it the other way around?
Modeling how biological complexity arises from simple rules
The complexity we see in biology derives from many simple interactions
Forward modeling or reverse modeling: from the top down or from the bottom up?
On the top or on the bottom? Modeling approaches reveal how you like it.
ps – should science really be so boring all the time? Most talk titles I see convey that sense. But given that we need to get more people interested in science, not less, how about we make it a little bit interesting from time to time?
pss – I invited well known antibiotic resistance researcher Bruce Levin (from Emory) to give an upcoming seminar in my department. He obviously “gets” this concept. His talk title?
“Sex and drugs: the population and evolutionary dynamics of recombination and antibiotic treatment in bacteria”
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