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From: dwc@aipna.ed.ac.uk (Dave W. Corne)
Newsgroups: comp.ai.neural-nets
Subject: Recognising Peaks in NMR Data
Keywords: NMR
Message-ID: <4253@aipna.ed.ac.uk>
Date: 4 Apr 91 14:35:25 GMT
Reply-To: dwc@aipna.ed.ac.uk (Dave W. Corne)
Organization: Dept of AI, Edinburgh University, UK.
Lines: 59

Hello everyone, 

 My brother wants to write a short paper suggesting how his
research group can use AI methods to find peaks in NMR data, 
and has asked me in particular about neural net methods -- 

 He's thinking of using NNs to learn the differences between real
peaks and noise; the problem is this: 

 "Perhaps the best way in which I can describe the NMR data
 is to draw the analogy with Ordnance Survey maps.  A 2D NMR
  spectrum is actually a "relief map" with (x,y) points which
  have an intensity (height): this is represented graphically as
  either a contour map (as per Ordnance Survey) or as a 3D 
  plot (relief map). The raw data are usually in the form
  of a 2D matrix (typically, 512 x 512 or 1024 x 512) of
  intensities - given the number of data points in the x- and
  y- directions and the total width in the x- and y-directions the
 (x,y) coordinates of each of the intensities in the matrix may be
 calculated:

     e.g. a small peak in a much larger matrix may be

            1 0 1 0 9 0 0 0 0
            0 1 9 0 1 9 0 0 1
            0 0 0 9 0 9 1 1 0
            0 1 1 9 9 0 1 0 1

   which represents a shape like : 

                    ~
                ~     ~
                 ~    ~
                 ~ ~

   and the 0's and 1's are "noise".

  Hopefully, noise peaks will have, in general, lower intensities,
  and real peaks will have particular shape characteristics.

   Does distinguishing between the peaks and the noise lend itself to
  NN methods? "

    If anyone out there has any thoughts, comments, ideas and/or 
 references that would help my brother out, we would be very pleased 
 to receive them. I`m sure Simon will be happy to discuss his research
 in more detail if anyone is interested. 

  Could you please send comments to simon@uk.ac.leeds.bio.vax, or me 
  at dwc@uk.ac.ed.aifh, or both, rather than (or in addition to ) 
  posting them here, as Simon doesn't have news access. 

   Thank you very much for reading this far, and we look forward
  to hearing some suggestions on this matter.

       
         Dave:   dwc@uk.ac.ed.aifh
on behalf of
         Simon:  simon@uk.ac.leeds.bio.vax