[R] is clustering analysis possible with R ?

[Maura E Monville]

I have 316 files storing a number of cycles of the respiratory signal
from 316 different patients. Each file record  is made up of the
following data:

 amplitude,phase,timestamp,validflag,ttlin,mark,ttlout

amplitude:  is the position in cm relative to an arbitrary reference
(signal amplitude)

phase:  is the phase value for the current sample (the time point at
which the breathing signal was recorded)

timestamp:  time of the sample measurement in milliseconds

validflag:  value of 0 indicates a valid track and a periodic signal,
and a value less than 0 indicates either a lost track,
              a bad video signal, or a non periodic signal

ttlin: is the bit value indicating the status of a sensed TTL signal.
Possible values include 1 (+5 VDC) and  0 (0 VDC).

mark:  specifies the sample when the phase value is closest to 0 or PI
(180 degrees) . Possible values include Z (0 phase), P (PI phase),
          "" (null string), and - (neither 0 nor PI phase)

ttl_out: is the bit value indicating the status of an output TTL
signal. Possible values include 1 (+5 VDC) and 0 (0 VDC)

The goal is to perform clustering analysis on such data, that is to
group togther those which have common characteristics. Which
characteristics and how many groups ... ??? ... well this is to be
found out.
Is R a good tool for analysing many data and find patterns common to
data subsets ?
Which other tool do you advice ?
Thank you very much,
-- 
Maura E.M