Identifying Branched Metabolic Pathways by Merging Linear Metabolic Pathways

摘要: This paper presents a graph-based algorithm for identifying complex metabolic pathways in multi-genome scale data. These are called branched because they can arrive at target compound through combinations of that split compounds into smaller ones, work parallel with many compounds, and join larger ones. While most previous has focused on linear pathways, predominate networks. Automatic identification number important applications areas require deeper understanding metabolism, such as engineering drug identification. Our utilizes explicit atom tracking to identify then merges them together pathways. We provide results two well-characterized demonstrate this new merging approach efficiently find biologically relevant structures.