Coregenes 5.0 makes use of the following tools and algorithms.

Coregenes 5.0 has been published! Please cite:

  1. Davis P, Seto D, Mahadevan P. (2022). CoreGenes5.0: An Updated User-Friendly Webserver for the Determination of Core Genes from Sets of Viral and Bacterial Genomes. Viruses 14, 2534.
If you use CoreGenes 5.0, please also cite the articles below.
  1. Contreras-Moreira, B., & Vinuesa, P. (2013). GET_HOMOLOGUES, a versatile software package for scalable and robust microbial pangenome analysis. Appl. Environ. Microbiol., 79(24), 7696-7701
  2. Ortho MCL Algorithm
  3. Li, L., Stoeckert, C. J., & Roos, D. S. (2003). OrthoMCL: identification of ortholog groups for eukaryotic genomes. Genome research, 13(9), 2178-2189.
  4. COG Triangle Algorithm:
  5. Kristensen DM, Kannan L, Coleman MK, Wolf YI, Sorokin A, Koonin EV, Mushegian A. 2010. A low-polynomial algorithm for assembling clusters of orthologous groups from intergenomic symmetric best matches. Bioinformatics 26:1481–1487

Coregenes 3.5 makes use of the following tools. If you use the Coregenes3.5 Iterative Comparison Algorithm, please cite the articles below.

  1. Turner D, Reynolds D, Seto D, Mahadevan P. (2013). CoreGenes3.5: a webserver for the determination of core genes from sets of viral and small bacterial genomes. BMC Res Notes. 6:140.
  2. Steinegger, M., & Söding, J. (2017). MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nature biotechnology, 35(11), 1026-1028.
  3. Zafar, N., Mazumder, R. and Seto, D. (2002). CoreGenes: A computational tool for identifying and cataloging "core" genes in a set of small genomes. BMC Bioinformatics 3:12.
  4. Mahadevan, P., King, J.F. and Seto, D. (2009). CGUG: in silico proteome and genome parsing tool for the determination of "core" and unique genes in the analysis of genomes up to ca. 1.9 Mb. BMC Research Methods 2:168.
  5. Mahadevan, P., King, J.F. and Seto, D. (2009). Data mining pathogen genomes using GeneOrder, CoreGenes and CGUG: gene order, synteny, and in silico proteomes. International Journal of Computational Biology and Drug Design 2:100-114.