Due to the ever-increasing size of sequence databases it has become clear that faster techniques must be employed to effectively perform biological sequence analysis in a reasonable amount of time. Exploiting the inherent parallelism between sequences is a common strategy. In this paper we enhance both the fine-grained and coursegrained parallelism within the HMMER [2] sequence analysis suite. Our strategies are complementary to one another and, where necessary, can be used as drop-in replacements to the strategies already provided within HMMER. We use conventional processors (Intel Pentium IV Xeon) as well as the freely available MPICH parallel programming environment [1]. Our results show that the MPICH implementation greatly outperforms the PVM HMMER implementation, and our SSE2 implementation also lends greater computational power at no cost to the user.