Machine learning methods for biotechnology applications

We have developed a series of machine learning methods for biotechnology applications. These include screening of large metabolic databases and prediction of catalytic activity from sequence.

Further readings on catalytic activity prediction and protein-chemical interactions

  • Carbonell P, Wong J, Swainston N, Takano E, Turner NJ, Scrutton NS, Kell DB, Breitling R, Faulon JL. Selenzyme: Enzyme selection tool for pathway design. Bioinformatics, 2018. | doi: 10.1093/bioinformatics/bty065
  • Jervis AJ, Carbonell P, Vinaixa M, Dunstan MS, Hollywood KA, Robinson CJ, Rattray NJW, Yan C, Swainston N, Currin A, Sung R, Toogood HS, Taylor S, Faulon JL, Breitling R, Takano E, Scrutton NS. Machine learning of designed translational control allows predictive pathway optimisation in Escherichia coli. ACS Synthetic Biology, 2018. | doi: 10.1021/acssynbio.8b00398 | PMID: 30563328
  • Mellor J, Grigoras I, Carbonell P, Faulon JL. Semi-supervised Gaussian Process for automated enzyme search. ACS Synthetic Biology, 5(6): 518-528, 2016. | doi: 10.1021/acssynbio.5b00294
  • Carbonell P, Lecointre G, Faulon JL. Origins of specificity and promiscuity in metabolic networks. Journal of Biological Chemistry, 286(51): 43994-44004, 2011. | doi: 10.1074/jbc.M111.274050
  • Carbonell P, Faulon JL. Molecular signatures-based prediction of enzyme promiscuity. Bioinformatics, 26(16): 2012-2019, 2010. | doi: 10.1093/bioinformatics/btq317
  • Misra M, Martin S, Faulon JL*. Graphs: Flexible Representations of Molecular Structures and Biological Networks, in Computational Approaches in Cheminformatics and Bioinformatics, Guha R., Bender, A. Edts, Wiley, 2012. | doi: 10.1002/9781118131411.ch6
  • Faulon JL, Misra M, Martin S, Sale K, Sapra R. Genome scale enzyme-metabolite and drug-target interaction predictions using the signature molecular descriptor. Bioinformatics. 2008 Jan 15;24(2):225-33. Epub 2007 Nov 23. | doi:  10.1093/bioinformatics/btm580
  • Martin S, Brown WM, Faulon JL*. Using product kernels to predict protein interactions. Advances in Biochemical Engineering/Biotechnology, 110:215-245, 2008. | doi: 10.1007/10_2007_084 | PMID: 17922100
  • Martin, S., Roe, D., Faulon, J.L. Predicting protein-protein interactions using signature products, Bioinformatics, 21(2):218-226, 2005. | doi: 10.1093/bioinformatics/bth483 | PMID: 15319262

The same techniques are also used to predict molecular activity and to design novel molecules.

  • Koch M, Duigou T, Carbonell P, Faulon JL. Molecular structures enumeration and virtual screening in the chemical space with RetroPath2.0. Journal of Cheminformatics, 9:64, 2017. | doi: 10.1186/s13321-017-0252-9
  • Jaghoori, M.M., Jongmans S.T.Q., de Boer, F., Peironcely, J., Faulon, J.L., Reijmers, T., Hankemeier, T. PMG: Multi-core metabolite identification. Electronic Notes in Theoretical Computer Science, 299: 53-60, 2013. | doi: 10.1016/j.entcs.2013.11.005
  • Planson, A.G., Carbonell, P., Paillard, E., Pollet, N., Faulon, J.L. Compound toxicity screening and structure-activity relationship modeling in Escherichia coli. Biotechnology and Bioengineering, 109(3): 846-850, 2012. | doi: 10.1002/bit.24356
  • Weis DC, Visco DP Jr, Faulon JL*. Data mining PubChem using a support vector machine with the Signature molecular descriptor: classification of factor XIa inhibitors. J Mol Graph Model. 2008 Nov;27(4):466-75. Epub 2008 Aug 27. | doi: 10.1016/j.jmgm.2008.08.004 | PMID: 18829357