  We applied computational tools for automatic detection of peculiar galaxy
pairs. We first detected in SDSS DR7 ~400,000 galaxy images with i magnitude
<18 that had more than one point spread function, and then applied a machine
learning algorithm that detected ~26,000 galaxy images that had morphology
similar to the morphology of galaxy mergers. That dataset was mined using a
novelty detection algorithm, producing a short list of 500 most peculiar
galaxies as quantitatively determined by the algorithm. Manual examination of
these galaxies showed that while most of the galaxy pairs in the list were not
necessarily peculiar, numerous unusual galaxy pairs were detected. In this
paper we describe the protocol and computational tools used for the detection
of peculiar mergers, and provide examples of peculiar galaxy pairs that were
detected.
