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Certain bioinformatics research, such as sequence alignment, alternative splicing, protein function/structure prediction, gene identify, bio-chip data analysis, and so on, requires massive computing power, which is hardly available in a single computing node. In order to facilitate bioinformatics research, we have designed and implemented a distributed and parallel computing environment with grid technology, in which, biologists can solve bioinformatics problems using distributed computing resources in parallel and reduce execution time. In this environment, the computing power and program information of computing nodes are described with XML documents. A web service named Local Resource Management Service is deployed on each computing node so that the distributed resources can be accessed in a uniform manner. With an API suite, biologists can use distributed computing resources in parallel easily in their applications. Further more, users can monitor the status of distributed resources dynamically on the portal. A real use case of alternative splicing is also presented, through which we have analyzed the usability, efficiency, and stability of the environment.