We present a catalogue of galaxy photometric redshifts and k-corrections for the Sloan Digital Sky Survey Data Release 7 (SDSS-DR7), available on the World Wide Web. The photometric redshifts were estimated with an artificial neural network using five ugriz bands, concentration indices and Petrosian radii in the g and r bands. We have explored our redshift estimates with different training sets, thus concluding that the best choice for improving redshift accuracy comprises the main galaxy sample (MGS), the luminous red galaxies and the galaxies of active galactic nuclei covering the redshift range 0 < z≤ 0.3. For the MGS, the photometric redshift estimates agree with the spectroscopic values within rms = 0.0227. The distribution of photometric redshifts derived in the range 0 < zphot≤ 0.6 agrees well with the model predictions.
k-corrections were derived by calibration of the k-correct_v4.2 code results for the MGS with the reference-frame (z= 0.1) (g−r) colours. We adopt a linear dependence of k-corrections on redshift and (g−r) colours that provide suitable distributions of luminosity and colours for galaxies up to redshift zphot= 0.6 comparable to the results in the literature. Thus, our k-correction estimate procedure is a powerful, low computational time algorithm capable of reproducing suitable results that can be used for testing galaxy properties at intermediate redshifts using the large SDSS data base.