Modeling the ribosome as a bipartite graph

Abstract

Developing mathematical representations of biological systems that can allow predictions is a challenging and important research goal. It is demonstrated here how the ribosome, the nano-machine responsible for synthesizing all proteins necessary for cellular life, can be represented as a bipartite network. Ten ribosomal structures from Bacteria and six from Eukarya are explored. Ribosomal networks are found to exhibit unique properties despite variations in the nodes and edges of the different graphs. The ribosome is shown to exhibit very large topological redundancies, demonstrating mathematical resiliency. These results can potentially explain how it can function consistently despite changes in composition and connectivity. Furthermore, this representation can be used to analyze ribosome function within the large machinery of network theory, where the degrees of freedom are the possible interactions, and can be used to provide new insights for translation regulation and therapeutics.

Snowflake: visualizing microbiome abundance tables as multivariate bipartite graphs

“…To transform the data into a microbiome composition graph and create a topological overview of the presence of an OTU/ASV in the collected samples, a relational structure is introduced to the data ( Figure 1 ). This transformation results in a bipartite graph, a common format in biological studies ( Li et al, 2020 ; Chi et al, 2021 ; Calvet, 2022 ), where every row (sample) and column (OTU/ASV) in the table becomes an object (node) stored in a node list. Objects for which a non-zero cell value exists (abundance 0), are linked, storing its absolute and relative abundances in a weight property.…”