This paper presents our preliminary work on adaptation of parsing technology toward natural language query processing for biomedical domain. We built a small treebank of natural language queries, and tested a state-of-theart parser, the results of which revealed that a parser trained on Wall-Street-Journal articles and Medline abstracts did not work well on query sentences. We then experimented an adaptive learning technique, to seek the chance to improve the parsing performance on query sentences. Despite the small scale of the experiments, the results are encouraging, enlightening the direction for effective improvement. 1