A Web Tool for Generating High Quality Machine-readable Biological Pathways

Abstract

PathWhiz is a web server built to facilitate the creation of colorful, interactive, visually pleasing pathway diagrams that are rich in biological information. The pathways generated by this online application are machine-readable and fully compatible with essentially all web-browsers and computer operating systems. It uses a specially developed, web-enabled pathway drawing interface that permits the selection and placement of different combinations of pre-drawn biological or biochemical entities to depict reactions, interactions, transport processes and binding events. This palette of entities consists of chemical compounds, proteins, nucleic acids, cellular membranes, subcellular structures, tissues, and organs. All of the visual elements in it can be interactively adjusted and customized. Furthermore, because this tool is a web server, all pathways and pathway elements are publicly accessible. This kind of pathway "crowd sourcing" means that PathWhiz already contains a large and rapidly growing collection of previously drawn pathways and pathway elements. Here we describe a protocol for the quick and easy creation of new pathways and the alteration of existing pathways. To further facilitate pathway editing and creation, the tool contains replication and propagation functions. The replication function allows existing pathways to be used as templates to create or edit new pathways. The propagation function allows one to take an existing pathway and automatically propagate it across different species. Pathways created with this tool can be "re-styled" into different formats (KEGG-like or text-book like), colored with different backgrounds, exported to BioPAX, SBGN-ML, SBML, or PWML data exchange formats, and downloaded as PNG or SVG images. The pathways can easily be incorporated into online databases, integrated into presentations, posters or publications, or used exclusively for online visualization and exploration. This protocol has been successfully applied to generate over 2,000 pathway diagrams, which are now found in many online databases including HMDB, DrugBank, SMPDB, and ECMDB.

HMDB 5.0: the Human Metabolome Database for 2022

“…Further improvements in HMDB’s pathway visualization tools have also continued with HMDB 5.0. Pathways images created by PathWhiz ( 28 ) as part of the PathBank project ( 29 ) have become increasingly standardized, more fully annotated and more visually sophisticated relative to the pathway images released in HMDB 4.0. PathWhiz is an online pathway drawing server which has been used to populate PathBank, which is a dedicated metabolomics pathway database covering many model organisms.…”

RTX-KG2: a system for building a semantically standardized knowledge graph for translational biomedicine

“…Name # Description Format Method Biolink [17,18] 1 Biolink Metamodel (semantic layer) TTL RBM ChEMBL [24,61] 1 EMBL Chemogenomic Database SQL D2J DGIdb [62] 1 Drug Gene Interaction Database TSV D2J DisGeNET [63] 1 Disease-Gene Associations TSV D2J DrugBank [23] 1 Pharmaceutical Knowledge Base XML D2J DrugCentral [64] 1 Online drug Compendium SQL D2J Ensembl Gene [65] 1 Ensembl Human Gene annotations JSON D2J EFO [57] 1 Experimental Factor Ontology OWL RBM GO [66,67] 1 Gene Ontology annotations TSV D2J HMDB [68][69][70][71] 1 Human Metabolite Database XML D2J IntAct [72,73] 1 IntAct Molecular Interaction Database TSV D2J Jensen Lab Diseases [74] 1 Gene to Diseases Dataset TSV D2J KEGG [21,75,76] 1 Kyoto Encyclopedia of Genes and Genomes API D2J miRBase [77][78][79][80][81] 1 MicroRNAs Dataset DAT D2J NCBI Gene [82] 1 NCBI Human Gene annotations TSV D2J OBO Foundry 21 OBO Foundry Ontologies (Table S1) OWL RBM Orphanet [83] 1 Orphanet Rare Disease Ontology OWL RBM PathBank [84][85][86] 1 Wishart Lab Pathway Databases XML D2J Reactome [87] 1 Pathway Database SQL D2J SemMedDB [29] 1 Semantic Medline Database SQL D2J SMPDB [26,27] 1 Small Molecule Pathway Database CSV D2J UMLS [88] 26 Unified Medical Language System (Table 3) TTL RBM UniChem…”

Hochdurchsatz‐Metabolomik mit 1D‐NMR

“…Weiterhin hat die Entwicklung von MSEA‐Methoden (metabolite set enrichment analysis) wesentlich geholfen, die Muster der Metabolitkonzentrationsänderungen in einem biologisch relevanten Kontext zu identifizieren und funktional und/oder biologisch zu interpretieren. Es gibt frei verfügbare Software, um diese Methoden zu implementieren . Zu diesen gehört MetaboAnalyst, ein umfassendes Programmpaket für NMR‐ und MS‐basierte Metabolomanalyse und ‐interpretation einschließlich Optionen für die metabolische Stoffwechselanalyse und MSEA.…”