In order to increase the performance of NDEx, we are experimenting several architectural changes that will be implemented in our next release. To begin with, we have optimized the storage data model so that network elements can be stored in the database faster. This is particularly important when creating large networks and the graphic below shows the results obtained when comparing performance with and without the improved storage data model. The time required to create 4 test network of increasing size is notably reduced thanks to the optimized storage data model (red bars) and this reduction appears more dramatic as the network size increases.
Network creation times are 2X faster for Test network 1, 3.5X faster for Test network 2, 10X faster for Test network 3 and about 4X faster for Test network 4.
Additional changes in NDEx v1.3 will include use of the external Solr indexes to handle network queries, making the NDEx server easier to scale up.
Towards a system-level understanding of the human microbiome
The advances in experimental methods and the development of high performance bioinformatic tools have substantially improved our understanding of microbial communities associated with human niches. September's featured article from Bikel and collaborators focuses on the importance and spearheads the challenges of combining metagenomics, metatranscriptomics and viromics approaches to achieve a system-level understanding of the human microbiome.
ESCHER is a web-based open source tool to build, view and share metabolic pathway maps. ESCHER will soon offer maps for all organisms included in the BIGG database and users can also decide to contribute their own maps. A few of demo maps are available on the ESCHER web site to showcase the tool's capabilities: for example, in the KNOCKOUT demo map, you can shutdown individual metabolic reactions in E.coli, see how pathways are altered and how these changes affect the bacterial growth rate. For detailed information, please check the ESCHER documentation.