TY - JOUR
T1 - Graph-based data integration from bioactive peptide databases of pharmaceutical interest
T2 - Toward an organized collection enabling visual network analysis
AU - Aguilera-Mendoza, Longendri
AU - Marrero-Ponce, Yovani
AU - Beltran, Jesus A.
AU - Tellez Ibarra, Roberto
AU - Guillen-Ramirez, Hugo A.
AU - Brizuela, Carlos A.
N1 - Publisher Copyright:
© 2019 The Author(s). All rights reserved.
PY - 2019/11/1
Y1 - 2019/11/1
N2 - Bioactive peptides have gained great attention in the academy and pharmaceutical industry since they play an important role in human health. However, the increasing number of bioactive peptide databases is causing the problem of data redundancy and duplicated efforts. Even worse is the fact that the available data is non-standardized and often dirty with data entry errors. Therefore, there is a need for a unified view that enables a more comprehensive analysis of the information on this topic residing at different sites. Results: After collecting web pages from a large variety of bioactive peptide databases, we organized the web content into an integrated graph database (starPepDB) that holds a total of 71 310 nodes and 348 505 relationships. In this graph structure, there are 45 120 nodes representing peptides, and the rest of the nodes are connected to peptides for describing metadata. Additionally, to facilitate a better understanding of the integrated data, a software tool (starPep toolbox) has been developed for supporting visual network analysis in a user-friendly way; providing several functionalities such as peptide retrieval and filtering, network construction and visualization, interactive exploration and exporting data options.
AB - Bioactive peptides have gained great attention in the academy and pharmaceutical industry since they play an important role in human health. However, the increasing number of bioactive peptide databases is causing the problem of data redundancy and duplicated efforts. Even worse is the fact that the available data is non-standardized and often dirty with data entry errors. Therefore, there is a need for a unified view that enables a more comprehensive analysis of the information on this topic residing at different sites. Results: After collecting web pages from a large variety of bioactive peptide databases, we organized the web content into an integrated graph database (starPepDB) that holds a total of 71 310 nodes and 348 505 relationships. In this graph structure, there are 45 120 nodes representing peptides, and the rest of the nodes are connected to peptides for describing metadata. Additionally, to facilitate a better understanding of the integrated data, a software tool (starPep toolbox) has been developed for supporting visual network analysis in a user-friendly way; providing several functionalities such as peptide retrieval and filtering, network construction and visualization, interactive exploration and exporting data options.
UR - http://www.scopus.com/inward/record.url?scp=85074965901&partnerID=8YFLogxK
U2 - 10.1093/bioinformatics/btz260
DO - 10.1093/bioinformatics/btz260
M3 - Artículo
C2 - 30994884
AN - SCOPUS:85074965901
SN - 1367-4803
VL - 35
SP - 4739
EP - 4747
JO - Bioinformatics
JF - Bioinformatics
IS - 22
ER -