Words to Perspective Students:
     Contemporary biology is dominated by words like "bioinformatics", "genomics" and "proteomics".  I wonder what Darwin would say.  Bioinformatics came into being because of technological advances in computer science and molecular biology, not because it has raised any fundamentally new questions in basic biology.  Biologists since before Darwin's time have always been interested in phenotypical and genetic variations.  But it takes a sexy acronym "SNPs" to make the study of genetic polymorphism become a public (and funding agency's) fascination.  (One example of what Steven Gould called "science by buzz words".  But Darwin was not preoccupied with developing billion-dollar blockbust drugs, or writing grants.)

     I was trained primarily in population genetics and biostatistics, and "bioinformatics" means to me nothing more than evolutionary analysis using modern computing systems.  In a few years from now, every biology Ph.D.'s will be a bioinformatician, in the sense that every biologist now is a chemist, or every modern astronomer/meteorologist is a computer technologist.  My message is, learn the latest technology, but the real intellectual satisfaction of working in the lab will hopefully come from biological understandings.

     Years ago I was attending a Gordon Conference on Microbial Population Biology.  In one session, somebody raised the question of the relative merit of experimental approach versus studying natural populations.  John Maynard Smith, being an ultimate evolutionary theoretician made a seemingly casual comment: "We don't need to do experiments.  The nature has done all."  The comment pretty much summed up about what has underlined my research approach, which is analyzing natural genome variations rather than treatment-based research.

     In joining the lab, you may expect to develop skills in three broadly categorized fields (in the order of expected learning time):
  • Computing.  You are going to learn the Gnu/Linux computing system, the standard Open Source platform for bioinformatics research today.  You also have the opportunity to learn Perl programming language, especially Bioperl, a collection of Perl libraries for biology applications. The concept of relational database and SQL is also useful to know about.
  • Biostatistics.  Statistics gives both strength and weakness to evolutionary bioinformatics.  Statistics is a strength because it is indispensible for dealing with the stochasticity of scientific data (and for publishing papers).  Heavy reliance on statistics, however, often seems a weakness of evolutionary informatics because of lack of certainty in conclusion.  However, when one realizes that there is no certainty even in that the Sun will rise again tomorrow, and understands that correlation is often far from causation, one may start to regard statistical uncertainty not as a source of frustration and anxiety, but a source of enlightened comfort, knowing that, after all, there are managible regularities in the face of unpredicability.  An Open Source statistical package called "R", is the main tool for statistical computing and graphing in the lab. 
  • Evolutionary biology.  It is useful to divide the study of molecular diversity into micro-evolutionary and macro-evolutionary questions.  The former is concerned with analysis of the genetic polymorphisms at the population level, and the later is the more popular field of molecular evolution, which studies mostly genetic divergence at higher taxonomical levels.  I am most interested in evolutionary changes happened within a relatively small time period (when the variance of these changes are also small), such as comparative genomics of two Borrelia strains.  Finally, taking a reductionist approach, I am more interested in the evolution of relatively simple organisms such as bacteria.  

     Students interested in joining the lab for doctoral thesis research will be advised to take classes in Unix computing, graduate statistics and population genetics.

     I will do my best to make the lab a place for developing practical (marketable) scientific skills (e.g. bio-computing and statistics), as well as scientifically productive.  I look forward to your intellectual contribution to the lab, and mostly, a fun and enjoyable life experience together.

     Sincerely,

     Weigang

     Dec. 6, 2002

Last update on Dec 6, 2002
By Weigang Qiu