A bioinformatics system for searching Co-Occurrence based on Co-Operational Formation with Advanced Method (COCOFAM)
This addresses the challenge for biomedical researchers in obtaining knowledge from vast literature, though it appears incremental as it builds on existing technologies like Spark.
The authors tackled the problem of efficiently searching massive biomedical literature by proposing COCOFAM, a novel system that integrates Spark and a global job scheduler to gather crowdsourced co-occurrence data, enabling users to access relevant information from large-scale literature.
Literature analysis is a key step in obtaining background information in biomedical research. However, it is difficult for researchers to obtain knowledge of their interests in an efficient manner because of the massive amount of the published biomedical literature. Therefore, efficient and systematic search strategies are required, which allow ready access to the substantial amount of literature. In this paper, we propose a novel search system, named Co-Occurrence based on Co-Operational Formation with Advanced Method(COCOFAM) which is suitable for the large-scale literature analysis. COCOFAM is based on integrating both Spark for local clusters and a global job scheduler to gather crowdsourced co-occurrence data on global clusters. It will allow users to obtain information of their interests from the substantial amount of literature.