Modulector: A platform-as-a-service for access to microRNA databases
DOI:
https://doi.org/10.24215/26838559e030Keywords:
microARN, gene expression regulation, bioinformatics, biomedical database, web platformAbstract
The remarkable growth in the volume of genomic data and the enormous variety of databases that store them make it essential to have efficient and effective integration mechanisms. Several tools are currently available that offer APIs (Application Programming Interfaces) that allow access to this information, which can be used both through programming languages and browsers from web services. However, in specific domains of bioinformatics such as the case of MicroRNAs -small RNA molecules of great interest due to their ability to regulate the activity of other genes- most of the solutions fall back on problems that make them difficult to use, including the lack of processes that simplify the updating of their databases as new information is published, inadequate response times, difficulty to guarantee scalability, lack of consistency in the data exchange format, extremely limited functionality, errors due to lack of maintenance, among other frequent problems.
This paper presents Modulector, a solution that integrates information from genomic databases with microARN (miRNA) databases to simplify access to the different dimensions of microRNA information of interest (sequences, drugs and associated pathologies, regulated genes, scientific publications), with special emphasis on solving the common technical problems described above.
Modulector provides access through a REST API (API Representational State Transfer), guarantees adequate response times and scalability, has sorting, filtering, searching, and pagination capabilities. The solution uses containers, simplifying deployment on any server, which makes it adaptable for most use cases where Modulector is to be used privately. All information returned by Modulector is normalized in JSON format, making it efficient for manipulation by any development tool. Modulector source code is available at https://github.com/omics-datascience/modulector.
Downloads
References
Agarwal, V., Bell, G.W., Nam, J. y Bartel, D.P. (2015). Predicting effective microRNA target sites in mammalian mRNAs. eLife, 4, e05005. https://doi.org/10.7554/eLife.05005
Chang, L., Zhou, G., Soufan, O. y Xia, J. (2020). miRNet 2.0 - network-based visual analytics for miRNA functional analysis and systems biology. Nucleic Acids Research, 48(W1), W244–W251. https://doi.org/10.1093/nar/gkaa467
Cho, S., Jang, I., Jun, Y., Yoon, S., Ko, M., Kwon, Y. y Lee, S. (2012). MiRGator v3. 0: a microRNA portal for deep sequencing, expression profiling and mRNA targeting. Nucleic Acids Research, 41(D1), D252-D257. https://doi.org/10.1093/nar/gks1168
Cho, S., Jun, Y., Lee, S., Choi, H. S., Jung, S., Jang, Y. y Kim, W. (2010). miRGator v2. 0: an integrated system for functional investigation of microRNAs. Nucleic Acids Research, 39(suppl_1), D158-D162. https://doi.org/10.1093/nar/gkq1094
Fan, Y, Siklenka, K., Arora, SK., Ribeiro, P., Kimmins, S. y Xia, J. (2016). miRNet - dissecting miRNA-target interactions and functional associations through network-based visual analysis. Nucleic Acids Research, 44, W135–141. https://doi.org/10.1093/nar/gkw288
Fan, Y. y Xia, J. (2018). miRNet: functional analysis and visual exploration of miRNA-target interactions in a network context. En: von Stechow, L., Santos Delgado, A. (eds) Computational Cell Biology. Methods in Molecular Biology, vol 1819. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8618-7_10
Fan, Y., Habib, M. y Xia, J. (2018). Xeno-miRNet: a comprehensive database and analytics platform to explore xeno-miRNAs and their potential targets. PeerJ. 6, e5650. https://doi.org/10.7717/peerj.5650
Fromm, B., Billipp, T., Peck, L. E., Johansen, M., Tarver, J. E., King, B. L. y Peterson, K. J. (2015). A uniform system for the annotation of vertebrate microRNA genes and the evolution of the human microRNAome. Annual Review of Genetics, 49, 213-242. https://doi.org/10.1146/annurev-genet-120213-092023
Griffiths-Jones, S. (2004). The microRNA Registry. Nucleic Acids Research, 32(suppl_1), D109–D111. https://doi.org/10.1093/nar/gkh023
Griffiths-Jones, S., Grocock R., Van Dongen S., Bateman A. y Enright A. (2006). miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Research, 34(suppl_1), D140–D144. https://doi.org/10.1093/nar/gkj112
Griffiths-Jones, S., Kaur Saini, H., Van Dongen, S. y Enright A. (2008). miRBase: tools for microRNA genomics. Nucleic Acids Research, 36(suppl_1), D154–D158. https://doi.org/10.1093/nar/gkm952
Huang, H.Y., Lin, Y.C., Li, J., Huang, K.Y., Shrestha, S., Hong, H.C., Tang, Y., Chen, Y.G., Jin, C.N., Yu, Y., Xu, J.T., Li, Y.M., Cai, X.X., Zhou, Z.Y., Chen, X.H., Pei, Y.Y., Hu, L., Su, J.J., Cui, S.D., ..., Huang, H.D. (2020). miRTarBase 2020: updates to the experimentally validated microRNA-target interaction database. Nucleic Acids Research, 48(D1), D148–D154. https://doi.org/10.1093/nar/gkz896
Huang, Z., Shi, J., Gao, Y., Cui, C., Zhang, S., Li, J., Zhou, Y. y Cui, Q. (2019). HMDD v3.0: a database for experimentally supported human microRNA-disease associations. Nucleic Acids Research, 47(D1), D1013–D1017. https://doi.org/10.1093/nar/gky1010
Jiang, Q., Wang, Y., Hao, Y., Juan, L., Teng, M., Zhang, X., Li, M., Wang, G. y Liu, Y. (2009). miR2Disease: a manually curated database for microRNA deregulation in human disease. Nucleic Acids Research, 37, D98-104. https://doi.org/10.1093/nar/gkn714
Johora, H., Hossain, G.S. y Kocerha, J. (2019). The potential for microRNA therapeutics and clinical research. Frontiers in Genetics, 10, 478. https://doi.org/10.3389/fgene.2019.00478
Kozomara, A. y Griffiths-Jones, S. (2011). miRBase: integrating microRNA annotation and deep-sequencing data, Nucleic Acids Research, 39(suppl_1), D152–D157. https://doi.org/10.1093/nar/gkq1027
Kozomara, A. y Griffiths-Jones, S. (2014). miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Research, 42(D1), D68–D73. https://doi.org/10.1093/nar/gkt1181
Kozomara, A., Birgaoanu, M. y Griffiths-Jones, S. (2019). miRBase: from microRNA sequences to function. Nucleic Acids Research, 47(D1), D155–D162. https://doi.org/10.1093/nar/gky1141
Licursi, V., Conte, F., Fiscon, G. y Paci, P. (2019). MIENTURNET: an interactive web tool for microRNA-target enrichment and network-based analysis. BMC Bioinformatics, 20, 545. https://doi.org/10.1186/s12859-019-3105-x
Miranda, K.C., Huynh, T., Tay, Y., Ang, Y.S., Tam, W.L., Thomson, A.M. y Rigoutsos, I. (2006). A pattern-based method for the identification of MicroRNA binding sites and their corresponding heteroduplexes. Cell, 126(6), 1203-1217. https://doi.org/10.1016/j.cell.2006.07.031
Ru, Y., Kechris, K., Tabakoff, B., Hoffman, P., Radcliffe, R., Bowler, R., Mahaffey, S., Rossi, S., Calin, G., Bemis, L. y Theodorescu, D. (2014). The multiMiR R package and database: integration of microRNA-target interactions along with their disease and drug associations. Nucleic Acids Research, 42(17), e133. https://doi.org/10.1093/nar/gku631
Ruepp, A., Kowarsch, A., Schmidl, D., Buggenthin, F., Brauner, B., Dunger, I., Fobo, G., Frishman, G., Montrone, C. y Theis, F.J. (2010). PhenomiR: a knowledgebase for microRNA expression in diseases and biological processes. Genome Biology, 11(1), R6. https://doi.org/10.1186/gb-2010-11-1-r6
Seungyoon, N., Bumjin, K., Seokmin, S. y Sanghyuk, L. (2007). miRGator: an integrated system for functional annotation of microRNAs. Nucleic Acids Research, 36(suppl_1), D159-D164. https://doi.org/10.1093/nar/gkm829
Shirdel, E.A., Xie, W., Mak, T.W. y Jurisica, I. (2011). NAViGaTing the Micronome. Using Multiple MicroRNA Prediction Databases to identify signalling pathway-associated MicroRNAs. PLoS ONE, 6(2), e17429. https://doi.org/10.1371/journal.pone.0017429
Tokar, T., Pastrello, C., Rossos, A.E.M., Abovsky, M., Hauschild, A.C., Tsay, M., Lu, R. y Jurisica, I. (2018). mirDIP 4.1-integrative database of human microRNA target predictions. Nucleic Acids Research, 46(D1), D360-D370. https://doi.org/10.1093/nar/gkx1144
Vlachos, I.S., Zagganas, K., Paraskevopoulou, M.D., Georgakilas, G., Karagkouni, D., Vergoulis, T., Dalamagas, T. y Hatzigeorgiou, A. G. (2015). DIANA-miRPath v3. 0: deciphering microRNA function with experimental support. Nucleic Acids Research, 43(W1), W460–W466. https://doi.org/10.1093/nar/gkv403
Wu, W. (2010). MicroRNA: potential targets for the development of novel drugs?. Drugs in R & D, 10(1), 1-8. https://doi.org/10.2165/11537800-000000000-00000
Xinyi, L., Shuyuan, W., Fanlin, M., Jizhe, W., Yan, Z., Enyu, D., Xuexin, Y., Xia, L., Wei, J. (2013). SM2miR: a database of the experimentally validated small molecules’ effects on microRNA expression. Bioinformatics, 29(3), 409–411. https://doi.org/10.1093/bioinformatics/bts698
Downloads
Published
How to Cite
Issue
Section
License
Los autores que publiquen en esta revista aceptan las siguientes condiciones:
La aceptación del manuscrito por parte de la revista implica la no presentación simultánea a otras revistas u órganos editoriales y la cesión no exclusiva de los derechos patrimoniales de los autores en favor del editor, quien permite la reutilización, luego de su edición (postprint), bajo licencia Creative Commons 4.0 (https://creativecommons.org/licenses/by-nc/4.0/deed.es). Usted es libre de:
1) Compartir, copiar y redistribuir el material en cualquier medio o formato.
2) Adaptar, remezclar, transformar y crear a partir del material, bajo los siguientes términos: 1) Atribución — Usted debe darle crédito a esta obra de manera adecuada, proporcionando un enlace a la licencia, e indicando si se han realizado cambios. Puede hacerlo en cualquier forma razonable, pero no de forma tal que sugiera que usted o su uso tienen el apoyo del licenciante. 2) Uso No Comercial — Usted no puede hacer uso del material publicado con fines comerciales.
Los autores pueden realizar otros acuerdos contractuales independientes y adicionales para la distribución no exclusiva de la versión del artículo publicado en esta revista (p. ej., incluirlo en un repositorio institucional o publicarlo en un libro) siempre que indiquen claramente que el trabajo se publicó por primera vez en esta revista.
La responsabilidad de cada trabajo publicado en cuanto a su contenido recae exclusivamente en los autores del mismo, deslindando a los editores de cualquier responsabilidad legal.
