Our Genomics experiments in this year mainly focus on improving the passage retrieval performance in the biomedical domain. We address this problem by constructing different indexes. In particular, we propose a method to build word-based index and sentence-based index for our experiments. The passage mean average precision (passage MAP) for our first run “york07ga1” using the word-based index was 0.095 and the passage MAP for our second run “york07ga2” using the sentence-based index was 0.086. However, the passage MAP for our third run “york07ga3” using both the word-based index and UMLS for query expansion degraded to 0.060. All these three official runs are automatic. The evaluation results show that using the word-based index is more effective than using the sentence-based index for improving the passage retrieval performance. We find that pseudo-relevance feedback can make a positive contribution to the retrieval performance. However, we also find that query expan...