CiSE: a circular spring embedder layout algorithm

SyBLaRS: A web service for laying out, rendering and mining biological maps in SBGN, SBML and more

Visualization is a key recurring requirement for effective analysis of relational data. Biology is no exception. It is imperative to annotate and render biological models in standard, widely accepted formats. Finding graph-theoretical properties of pathways as well as identifying certain paths or subgraphs of interest in a pathway are also essential for effective analysis of pathway data. Given the size of available biological pathway data nowadays, automatic layout is crucial in understanding the graphical representations of such data. Even though there are many available software tools that support graphical display of biological pathways in various formats, there is none available as a service for on-demand or batch processing of biological pathways for automatic layout, customized rendering and mining paths or subgraphs of interest. In addition, there are many tools with fine rendering capabilities lacking decent automatic layout support.

To fill this void, we developed a web service named SyBLaRS (Systems Biology Layout and Rendering Service) for automatic layout of biological data in various standard formats as well as construction of customized images in both raster image and scalable vector formats of these maps. Some of the supported standards are more generic such as GraphML and JSON, whereas others are specialized to biology such as SBGNML (The Systems Biology Graphical Notation Markup Language) and SBML (The Systems Biology Markup Language). In addition, SyBLaRS supports calculation and highlighting of a number of well-known graph-theoretical properties as well as some novel graph algorithms turning a specified set of objects of interest to a minimal pathway of interest.

We demonstrate that SyBLaRS can be used both as an offline layout and rendering service to construct customized and annotated pictures of pathway models and as an online service to provide layout and rendering capabilities for systems biology software tools.

SyBLaRS is open source and publicly available on GitHub and freely distributed under the MIT license. In addition, a sample deployment is available here for public consumption.

RiceNCexp: a rice non-coding RNA co-expression atlas based on massive RNA-seq and small-RNA seq data

Non-coding RNAs (ncRNAs) play important roles in regulating expression of protein-coding genes. Although gene expression databases have emerged in a timely manner, a comprehensive expression database for ncRNAs is still lacking. Herein, we constructed a rice ncRNA co-expression atlas (RiceNCexp), based on 491 RNA-seq and 274 small RNA (sRNA)-seq datasets. RiceNCexp hosts four types of ncRNAs, namely lncRNAs, PHAS genes, miRNAs, and phasiRNAs. RiceNCexp provides comprehensive expression information for rice ncRNAs in 22 tissues/organs, an efficient tau-based mining tool for tissue-specific ncRNAs, and the robust co-expression analysis among ncRNAs or between ncRNAs and protein-coding genes, based on 116 pairs of RNA-seq and sRNA-seq libraries from the same experiments. In summary, RiceNCexp is a user-friendly and comprehensive rice ncRNA co-expression atlas and can be freely accessed at https://cbi.njau.edu.cn/RiceNCexp/.

RSDB: A rare skin disease database to link drugs with potential drug targets for rare skin diseases

Rare skin diseases include more than 800 diseases affecting more than 6.8 million patients worldwide. However, only 100 drugs have been developed for treating rare skin diseases in the past 38 years. To investigate potential treatments through drug repurposing for rare skin diseases, it is necessary to have a well-organized database to link all known disease causes, mechanisms, and related information to accelerate the process. Drug repurposing provides less expensive and faster potential options to develop treatments for known diseases. In this work, we designed and constructed a rare skin disease database (RSDB) as a disease-centered information depository to facilitate repurposing drug candidates for rare skin diseases. We collected and integrated associated genes, chemicals, and phenotypes into a network connected by pairwise relationships between different components for rare skin diseases. The RSDB covers 891 rare skin diseases defined by the Orphanet and GARD databases. The organized network for each rare skin disease comprises associated genes, phenotypes, and chemicals with the corresponding connections. The RSDB is available at https://rsdb.cmdm.tw .

Automatic Polygon Layout for Primal-Dual Visualization of Hypergraphs

N-ary relationships, which relate $N$ entities where $N$ is not necessarily two, can be visually represented as polygons whose vertices are the entities of the relationships. Manually generating a high-quality layout using this representation is labor-intensive. In this paper, we provide an automatic polygon layout generation algorithm for the visualization of N-ary relationships. At the core of our algorithm is a set of objective functions motivated by a number of design principles that we have identified. These objective functions are then used in an optimization framework that we develop to achieve high-quality layouts. Recognizing the duality between entities and relationships in the data, we provide a second visualization in which the roles of entities and relationships in the original data are reversed. This can lead to additional insight about the data. Furthermore, we enhance our framework for a joint optimization on the primal layout (original data) and the dual layout (where the roles of entities and relationships are reversed). This allows users to inspect their data using two complementary views. We apply our visualization approach to a number of datasets that include co-authorship data and social contact pattern data.