  We report the development of a proton identification method for the
Super-Kamiokande detector. This new tool is applied to the search for events
with a single proton track, a high purity neutral current sample of interest
for sterile neutrino searches. After selection using a neural network, we
observe 38 events in the combined SK-I and SK-II data corresponding to 2285.1
days of exposure, with an estimated signal to background ratio of 1.6 to 1.
Proton identification was also applied to a direct search for charged-current
quasi-elastic (CCQE) events, obtaining a high precision sample of fully
kinematically reconstructed atmospheric neutrinos, which has not been
previously reported in water Cherenkov detectors. The CCQE fraction of this
sample is 55%, and its neutrino (as opposed to anti-neutrino) fraction is
91.7+/-3%. We selected 78 mu-like and 47 e-like events in the SK-I and SK-II
data set. With this data, a clear zenith angle distortion of the neutrino
direction itself is reported in a sub-GeV sample of muon neutrinos where the
lepton angular correlation to the incoming neutrino is weak. Our fit to
nu_mu->nu_tau oscillations using the neutrino L/E distribution of the CCQE
sample alone yields a wide acceptance region compatible with our previous
results and excludes the no-oscillation hypothesis at 3 sigma.
