[Rd] new book

Robert Gentleman rgentlem@jimmy.harvard.edu
Wed, 30 May 2001 10:45:44 -0400


On Wed, May 30, 2001 at 07:31:48AM -0700, A.J. Rossini wrote:
> >>>>> "MP" == Martyn Plummer <plummer@iarc.fr> writes:
> 
>     MP> This came up a couple of weeks ago on Slashdot (which I should
>     MP> really stop reading).  I got the impression from the ensuing
>     MP> discussion that it was targetted at biologists,but if you
>     MP> found it useful I shall pick up a copy.  In the same
>     MP> discussion, the monograph "Biological sequence analysis:
>     MP> probabilistic methods of proteins and nucleic acids" by Durbin
>     MP> (ed) was highly recommended by some people.  Do you have this?
> 
>     MP> Here is a link to the O'Reilly site which contains contents,
>     MP> and a sample chapter.
> 
>     MP> http://www.oreilly.com/catalog/bioskills/
> 
>     MP> I remember buying an O'Reilly book called "The whole internet:
>     MP> a users guide and catalogue". I wonder if this one will have
>     MP> an even shorter shelf life.
> 
> I commented privately, but since this comes up, I'll comment again: if
> you know your way around genetic programs, perl and bioperl, and
> understand general scripting tools, and have a smattering of
> informatics knowledge, the book isn't too useful.  I've got a
> protein-folding friend who plans on using it to teach a comp bio
> course in microbiology; he considers the skills mentioned in the book
> to be the bare-minimum for that, though it's short on theory.
> 

   I agree, but for those who are just getting started -- especially
   statistics grad students (or biology grad students or comp. sci) it
   can be very useful.
   I am actually a bit tempted to use it as a text for 1st year
   MSc/PhD's here, intro to stat computing. At least it gives them
   some examples that are relevant (and most know no Unix and no Perl
   and no....)

> The Durbin book is a nice intro to current state of the art DNA and
> protein sequencing methods, but not much more (of course, it lives up
> to its title).  That being said, I found it incredibly useful for
> seeing what has been done recently.  YMMV.
> 
  Yes, and Gusfield -- Algorithms on Strings Trees and Sequences is
  reasonable for what it does as well.

> I think part of the problem, and this is seen by those who recommend
> the Durbin book, is that there are a number of different ways of
> looking at the "bioinformatics" problem.  Problematically, you've got
> something like:
> 
> A. Large quantities of data, and handling, storage, backup
> B. Annotations and external (data) linkages

  I know very little about B. and found that DBCS at least gives some
  idea of what is available, what it looks like and how you might
  begin to deal with it.

  Yes, the field is developing so rapidly that it is useful now and
  won't be as good in 6 months and probably will be useless in 12 or
  18, but then so will the machine I'm typing at. 

> C. Computational Biology
> D. Statistical issues (experimental design/analysis and exploratory
>    approaches; 
> E. Combinations of the above two, including such topics (one of many
>    examples): stochastic DE modelling using mixed effects models.
> 
> and scientifically, you've got one or more of:
> 
> 1. sequencing (DNA and/or protein)
> 2. protein structure (secondary/tertiary, based on the above)
> 3. gene expression arrays of many forms (cDNA, membrane, gold,
>    oligios). 
> 4. SNPs 
> 5. genetics and evolutionary biology
> 
> and then there is the application area (cancer, HIV, other chronic
> diseases; comparative studies and animal/plant/non-human organism
> models, etc).
> 
> The classifications that I use are even up for grabs, depending on who
> you are and who you talk with; it's just 2 possible views of this high
> buzzword content area, sigh.  I know I've left out a few areas, here.
> 
> best,
> -tony
> 
> -- 
> A.J. Rossini				Rsrch. Asst. Prof. of Biostatistics
> U. of Washington Biostatistics		rossini@u.washington.edu	
> FHCRC/SCHARP/HIV Vaccine Trials Net	rossini@scharp.org
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