49
Views
0
CrossRef citations to date
0
Altmetric
Research Article

GSLAlign: community detection and local PPI network alignment

&
Received 09 Sep 2023, Accepted 29 Dec 2023, Published online: 12 Jan 2024

References

  • Ayub, U., Haider, I., & Naveed, H. (2020). Salign–a structure aware method for global ppi network alignment. BMC Bioinformatics, 21(1), 500. https://doi.org/10.1186/s12859-020-03827-5
  • Ayub, U., & Naveed, H. (2022). Bioalign: An accurate global ppi network alignment algorithm. Evolutionary Bioinformatics Online, 18, 11769343221110658. https://doi.org/10.1177/11769343221110658
  • Bainbridge, M. N., Warren, R. L., Hirst, M., Romanuik, T., Zeng, T., Go, A., Delaney, A., Griffith, M., Hickenbotham, M., Magrini, V., Mardis, E. R., Sadar, M. D., Siddiqui, A. S., Marra, M. A., & Jones, S. J. M. (2006). Analysis of the prostate cancer cell line lncap transcriptome using a sequencing-by-synthesis approach. BMC Genomics, 7(1), 246. https://doi.org/10.1186/1471-2164-7-246
  • Ciriello, G., Mina, M., Guzzi, P. H., Cannataro, M., & Guerra, C. (2012). Alignnemo: A local network alignment method to integrate homology and topology. PLoS One, 7(6), e38107. https://doi.org/10.1371/journal.pone.0038107
  • Erten, S., Li, X., Bebek, G., Li, J., & Koyutürk, M. (2009). Phylogenetic analysis of modularity in protein interaction networks. BMC Bioinformatics, 10(1), 333. https://doi.org/10.1186/1471-2105-10-333
  • Fields, S., & Song, O. K. (1989). A novel genetic system to detect protein–protein interactions. Nature, 340(6230), 245–246. https://doi.org/10.1038/340245a0
  • Girvan, M., & Newman, M. E. (2002). Community structure in social and biological networks. Proceedings of the National Academy of Sciences of the United States of America, 99(12), 7821–7826. https://doi.org/10.1073/pnas.122653799
  • Goh, C. S., & Cohen, F. E. (2002). Co-evolutionary analysis reveals insights into protein–protein interactions. Journal of Molecular Biology, 324(1), 177–192. https://doi.org/10.1016/s0022-2836(02)01038-0
  • Guzzi, P. H., & Milenkovic, T. (2018). Survey of local and global biological network alignment: The need to reconcile the two sides of the same coin. Briefings in Bioinformatics, 19(3), 472–481. https://doi.org/10.1093/bib/bbw132
  • Guzzi, P. H., Veltri, P., Roy, S., & Kalita, J. K. (2015). Modula: A network module based local protein interaction network alignment method. 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 1620–1623). IEEE. https://doi.org/10.1109/BIBM.2015.7359918
  • Hamilton, W., Ying, Z., & Leskovec, J. (2017). Inductive representation learning on large graphs. Advances in Neural Information Processing Systems, 30, 1–11. https://proceedings.neurips.cc/paper_files/paper/2017/file/5dd9db5e033da9c6fb5ba83c7a7ebea9-Paper.pdf
  • Jancura, P., Mavridou, E., Carrillo-de Santa Pau, E., & Marchiori, E. (2012). A methodology for detecting the orthology signal in a ppi network at a functional complex level. BMC Bioinformatics, 13(10), S18. https://doi.org/10.1186/1471-2105-13-S10-S18
  • Kalaev, M., Smoot, M., Ideker, T., & Sharan, R. (2008). Networkblast: Comparative analysis of protein networks. Bioinformatics (Oxford, England), 24(4), 594–596. https://doi.org/10.1093/bioinformatics/btm630
  • Kamran, A. B., & Naveed, H. (2022). Gontosim: A semantic similarity measure based on lca and common descendants. Scientific Reports, 12(1), 3818. https://doi.org/10.1038/s41598-022-07624-3
  • Kazemi, E., Hassani, H., Grossglauser, M., & Modarres, H. P. (2016). Proper: Global protein interaction network alignment through percolation matching. BMC Bioinformatics, 17(1), 527. https://doi.org/10.1186/s12859-016-1395-9
  • Koyutürk, M., Kim, Y., Topkara, U., Subramaniam, S., Szpankowski, W., & Grama, A. (2006). Pairwise alignment of protein interaction networks. Journal of Computational Biology: A Journal of Computational Molecular Cell Biology, 13(2), 182–199. https://doi.org/10.1089/cmb.2006.13.182
  • Li, B., Qing, T., Zhu, J., Wen, Z., Yu, Y., Fukumura, R., Zheng, Y., Gondo, Y., & Shi, L. (2017). A comprehensive mouse transcriptomic bodymap across 17 tissues by rna-seq. Scientific Reports, 7(1), 4200. https://doi.org/10.1038/s41598-017-04520-z
  • Lin, D. (1998). An information-theoretic definition of similarity. ICML, 98, 296–304.
  • Maskey, S., & Cho, Y. R. (2019). Leprimalign: Local entropy-based alignment of ppi networks to predict conserved modules. BMC Genomics, 20(9), 964. https://doi.org/10.1186/s12864-019-6271-3
  • Meng, L., Striegel, A., & Milenković, T. (2016). Local versus global biological network alignment. Bioinformatics (Oxford, England), 32(20), 3155–3164. https://doi.org/10.1093/bioinformatics/btw348
  • Milano, M., Guzzi, P. H., & Cannataro, M. (2018). Glalign: A novel algorithm for local network alignment. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 16(6), 1958–1969. https://doi.org/10.1109/TCBB.2018.2830323
  • Mina, M., & Guzzi, P. H. (2012). Alignmcl: Comparative analysis of protein interaction networks through Markov clustering. 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops (pp. 174–181). IEEE.
  • Nepusz, T., Yu, H., & Paccanaro, A. (2012). Detecting overlapping protein complexes in protein-protein interaction networks. Nature Methods, 9(5), 471–472. https://doi.org/10.1038/nmeth.1938
  • Pache, R. A., Céol, A., & Aloy, P. (2012). Netaligner–a network alignment server to compare complexes, pathways and whole interactomes. Nucleic Acids Research, 40, W157–W161. https://doi.org/10.1093/nar/gks446
  • Palla, G., Derényi, I., Farkas, I., & Vicsek, T. (2005). Uncovering the overlapping community structure of complex networks in nature and society. Nature, 435(7043), 814–818. https://doi.org/10.1038/nature03607
  • Patil, A., & Nakamura, H. (2005). Hint: A database of annotated protein-protein interactions and their homologs. Biophysics (Nagoya-Shi, Japan), 1, 21–24. https://doi.org/10.2142/biophysics.1.21
  • Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., & Duchesnay, E. (2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12, 2825–2830.
  • Que, X., Checconi, F., Petrini, F., & Gunnels, J. A. (2015). Scalable community detection with the Louvain algorithm. 2015 IEEE International Parallel and Distributed Processing Symposium (pp. 28–37). IEEE.
  • Resnik, P. (1999). Semantic similarity in a taxonomy: An information-based measure and its application to problems of ambiguity in natural language. Journal of Artificial Intelligence Research, 11, 95–130. https://doi.org/10.1613/jair.514
  • Schlicker, A., Domingues, F. S., Rahnenführer, J., & Lengauer, T. (2006). A new measure for functional similarity of gene products based on gene ontology. BMC Bioinformatics, 7(1), 302. https://doi.org/10.1186/1471-2105-7-302
  • Stark, C., Breitkreutz, B. J., Reguly, T., Boucher, L., Breitkreutz, A., & Tyers, M. (2006). Biogrid: A general repository for interaction datasets. Nucleic Acids Research, 34, D535–D539. https://doi.org/10.1093/nar/gkj109
  • Szklarczyk, D., Gable, A. L., Nastou, K. C., Lyon, D., Kirsch, R., Pyysalo, S., Doncheva, N. T., Legeay, M., Fang, T., Bork, P., Jensen, L. J., & von Mering, C. (2021). The string database in 2021: Customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Research, 49(18), 10800–1D612. https://doi.org/10.1093/nar/gkab835
  • Traag, V. A., Waltman, L., & Van Eck, N. J. (2019). From Louvain to Leiden: Guaranteeing well-connected communities. Scientific Reports, 9(1), 5233. https://doi.org/10.1038/s41598-019-41695-z
  • Wang, J. Z., Du, Z., Payattakool, R., Yu, P. S., & Chen, C. F. (2007). A new method to measure the semantic similarity of go terms. Bioinformatics (Oxford, England), 23(10), 1274–1281. https://doi.org/10.1093/bioinformatics/btm087
  • Zhao, C., & Wang, Z. (2018). Gogo: An improved algorithm to measure the semantic similarity between gene ontology terms. Scientific Reports, 8(1), 15107. https://doi.org/10.1038/s41598-018-33219-y

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.