The Volume 29 Number 1 January 2011 issue of nature biotechnology (www.nature.com/naturebiotechnology) finally puts in print what I’ve been recommending all along. The Feature article on computational BIOLOGY, “Trends in computation biology – 2010” on page 45 states, “Interviews with leading scientists highlight several notable breakthroughs in computational biology from the past year and suggest areas where computation may drive biological discovery,”
The researchers were asked to nominate papers of particular interest published in the previous year that have influenced the direction of their research.
The article is good, but what was really interesting was Box 2 – Cross-functional individuals on page 49. To quote, “Our analysis…suggests that researchers of a particular type are driving much of cutting-edge computational biology. Read on to find out what characterizes them.”
I’m going to re-print Box 2 Cross-functional individuals in it’s entirety since it’s short and the message is so very important.
Box 2 Cross-functional individuals
In the courses of compiling this survey, several investigators remarked that it tends to be easier for computer scientists to learn biology that for biologists to learn computer science. Even so, it is hard to believe that learning the central dogma and the Krebs cycle will enable your typical programmer-turned-computational biologist to stumble upon a project that yields important novel biological insights. So what characterizes successful computational biologists?
George Church, whose laboratory at Harvard Medical School (Cambridge, MA USA) has a history of producing bleeding-edge research in many cross-disciplinary domains, including computational biology, say, “Individuals in my lab tend to be curious and somewhat dissatisfied with the way things are. They are comfortable in two domains simultaneously. This has allowed us to go after problems in the space between traditional research projects.”
A former Church lab member, Greg Porreca, articulates this idea further, “I’ve found that many advances in computational biology start with simple solutions written by cross-functional individuals to accomplish simple tasks. Bigger problems are hard to address with those rudimentary algorithms, so folks with classical training in computer science step in and devise highly optimized solutions that are faster and more flexible.”
An overarching theme that also emerges from this survey suggests that tools for computational analysis permeated biological research according to three states: first, a cross-functional individual sees a problem and devises a solution good enough to demonstrate the feasibility of a type of analysis; second, robust tools are created, often utilizing the specialized knowledge of formally trained computer scientists; and third, the tools reach biologists focused on understanding specific phenomena, who incorporate the tools into everyday use. These stages echo existing broader literature on disruptive innovations1 and technology-adoption life cycles2,3, which may suggest how breakthroughs in computational biology can be nurtured.
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Christiansen, C.M. & Bower, J.I., Disruptive technologies: catching the wave. Harvard Business Review (1995).
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Moore, G.A. Crossing the Chase: Marketing and Selling High-Tech Products to Mainstream Customers (Harvard Business, 1999)
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Rogers, E.M. Diffusion of Innovations (Free Press, 2003).
Biologists must become aware of what the disciplines of computer science and engineering can offer computational biology. Until this happens, forward progress in computational biological innovations and discovery will be unnecessarily hampered by a number of superfluous factors not the least of which is complacence.
A Commentary piece, “Science Communication Revisited”, in the June, 2009, issue of Nature Biotechnology discusses increasing public involvement in science issues and decision-making.
Concerns are raised about the state of science education and scientific literacy more generally.
If only the public were more knowledgeable about things scientific, the article states, they would see things through the eyes of the expert.
Education
I was fortunate enough to have attended private schools from elementary through high school. Very few children are so lucky.
My biology teacher was a Catholic nun. She introduced us to Teilhard de Chardin (http://en.wikipedia.org/wiki/Pierre_Teilhard_de_Chardin).
Teilhard was a Jesuit priest who was trained as a paleontologist and geologist and took part in the discovery of Peking Man. He also studied botany and zoology. His book, The Phenomenon of Man, talks about the unfolding of the material cosmos towards the Omega Point, a maximum level of consciousness, that is pulling all creation towards it. Evolution, according to Teilhard, was the process of matter becoming aware of itself.
Therefore, I was able to receive a fairly sound exposure to evolution. On the other hand, the chapters on male and female biology and the reproductive process was ripped out of my text book.
(I know, because we found an unaltered book and read that forbidden text.)
At any rate, I grew up in an agricultural environment and knew what it was all about.
If you’re interested in the state of scientific education or education in public schools in Texas, I recommend the Texas Freedom Network (http://txfree.convio.net/site/PageServer ).
Experts
Concerning experts, I remember my section chief telling me, “You have to forgive Bryan, he still believes in experts.” Brian was our lead engineer.
As far as experts go, you have to be able to separate the good from the bad.
I recommend this article, Crap Detection 101 (http://www.sfgate.com/cgi-bin/blogs/rheingold/detail?entry_id=42805) and the CRAP Test (http://www.workliteracy.com/the-crap-test).
The CRAP test is a way to evaluate an internet source based on the following criteria: Currency, Reliability, Authority and Purpose/Point of View.
The article and test’s main focus is the internet — how to tell real from bogus. It’s not too hard to extrapolate the points they make to everyday life.
Scientific Literacy
Science and technology are changing so rapidly, that many people have simply given up on trying to keep up. Their scientific literacy consists of newspaper articles or blurbs on the TV news.
A lot of what is presented as science on network television is implausible (not to mention the technology used on these shows).
I think to really succeed, real scientists must pay attention to what is presented to the general public and critique it through publications, such as letters to the editor, blogs, appearances, etc. as much as possible.
Scientists should also by of an open mind as to the intelligence of your audience.
We have way too many people with 200 point IQ levels digging ditches in this country. We spend an inordinate amount of funds and interest on educating special children. We should be spending just as much time and funds (if not more) identifying and encouraging the geniuses among us who find education boring and quickly loose interest.
The interest in science is out there, but scientists must take an interest in how what passs for science is disseminated, validate or invalidate that science, identify the appropriate target audience, and address that audience level to really open up the forum on true scientific communication.
Salon, an e-zine, has a really good article. Why America is flunking science (http://www.salon.com/env/feature/2009/07/13/science_illiteracy/?source=newsletter) that is worth the read.
Here’s another link where the author lists current “myths” surrounding scientists engaging with the media.
http://scienceblogs.com/christinaslisrant/2009/07/when_discussing_scientists_eng.php