Topology of molecular interaction networks.

Molecular interactions are often represented as network models which have become the common language of many areas of biology. Graphs serve as convenient mathematical representations of network models and have themselves become objects of study. Their topology has been intensively researched over the last decade after evidence was found that they share underlying design principles with many other types of networks.

Efficient calculation of compound similarity based on maximum common subgraphs and its application to prediction of gene transcript levels.

Properties of a chemical entity, both physical and biological, are related to its structure. Since compound similarity can be used to infer properties of novel compounds, in chemoinformatics much attention has been paid to ways of calculating structural similarity. A useful metric to capture the structural similarity between compounds is the relative size of the Maximum Common Subgraph (MCS).

Integrating genome assemblies with MAIA.

Motivation: De novo assembly of a eukaryotic genome with next-generation sequencing data is still a challenging task. Over the past few years several assemblers have been developed, often suitable for one specific type of sequencing data. The number of known genomes is expanding rapidly, therefore it becomes possible to use multiple reference genomes for assembly projects.