Path: utzoo!utgpu!news-server.csri.toronto.edu!rpi!usc!apple!bionet!sass.sari.ac.uk!frank From: frank@sass.sari.ac.uk (Frank Wright) Newsgroups: bionet.software Subject: Re: more on knowing computers Message-ID: <8176.9104051141@sass.sari.ac.uk> Date: 5 Apr 91 11:41:44 GMT Sender: daemon@genbank.bio.net Lines: 35 I agree entirely with Michael Gribskov's comment..... "My perception is that, currently, broad conclusions about the function, evolution and structure of macromolecules are being made based on sequence similarity and inferred homology. Few graduate programs provide the training to critically evaluate such claims, and many people are left to either take the claim on faith or to reject it as unimportant." I'm writing a short "introduction to sequence analysis" course for Molecular Biologists at Scottish Agricultural Research Interests and am keen to stress that sequence *analysis* is really what they are doing, and that *computing* is simply the means to this end. I feel this is necessary given the use of "BioComputing" and/or "Molecular Biology Computing" to describe the activity of sequence analysis as well as the technology that makes it all possible. Sequence analysis often involves formulating a model, and analysing the data assuming that the model is valid. For example, database searching programs are implementations of algorithms that make assumptions about evolutionary processes. Tradeoffs between biological reality and mathematical tractability or CPU time are necessary. Users should be aware of these when interpreting output. Some knowledge of subjects like protein structure and evolution are required when carrying out and interpreting such complex analyses. ..and possibly also statistics... but I realise it's not a word that one uses nowadays. I avoid it by using "predict", "sequence analysis", "structure analysis",etc... It stops people's eyes glazing over. :-) Frank Wright SASS Molecular Biology Support Edinburgh University, Scotland e-mail: frank@sass.sari.ac.uk