Updated reference for SMILES string kernel

notebooks/Protein Fitness Prediction - Bag of Amino Acids.ipynb

@@ -7,7 +7,7 @@
    "source": [
     "# GP Regression on Protein Sequences: Bag of Amino Acids #\n",
     "\n",
-    "An example notebook for Tanimoto kernel-based GP regression on a dataset of protein sequences using a bag-of-amino acids representation of the protein sequence (analagous to the bag-of-SMILES model for molecules). The protein dataset consists of 151 sequences with a 'fitness' function (target label) of the melting point in degrees Celcius. The dataset is collated from values reported in references [1,2,3]. The sequences are each of length 290. For the Subsequence String Kernel (SSK) GP model see the 'GP Regression on Protein Sequences' notebook."
+    "An example notebook for Tanimoto kernel-based GP regression on a dataset of protein sequences using a bag-of-amino acids representation of the protein sequence (analagous to the bag-of-SMILES model for molecules). It should be noted that the bag-of-amino acids is equivalent to the SMILES string kernel from [1]. The protein dataset consists of 151 sequences with a 'fitness' function (target label) of the melting point in degrees Celcius. The dataset is collated from values reported in references [2,3,4]. The sequences are each of length 290. For the Subsequence String Kernel (SSK) GP model see the 'GP Regression on Protein Sequences' notebook."
    ]
   },
   {
@@ -376,11 +376,13 @@
    "source": [
     "## References\n",
     "\n",
-    "[1] Cui, Y., Chen, Y., Liu, X., Dong, S., Tian, Y.E., Qiao, Y., Mitra, R., Han, J., Li, C., Han, X. and Liu, W., 2021. [Computational redesign of a PETase for plastic biodegradation under ambient condition by the GRAPE strategy](https://pubs.acs.org/doi/abs/10.1021/acscatal.0c05126). ACS Catalysis, 11(3), pp.1340-1350.\n",
+    "[1] D-S Cao, J-C Zhao, Y-N Yang, C-X Zhao, J Yan, S Liu, Q-N Hu, Q-S Xu, and Y-Z Liang. [In silico toxicity prediction by support vector machine and SMILES representation-based string kernel](https://pubmed.ncbi.nlm.nih.gov/22224501/). SAR and QSAR in Environmental Research, 2012\n",
     "\n",
-    "[2] Liu, B., He, L., Wang, L., Li, T., Li, C., Liu, H., Luo, Y. and Bao, R., 2018. [Protein crystallography and site‐direct mutagenesis analysis of the poly (ethylene terephthalate) hydrolase PETase from Ideonella sakaiensis](https://chemistry-europe.onlinelibrary.wiley.com/doi/abs/10.1002/cbic.201800097). ChemBioChem, 19(14), pp.1471-1475.\n",
+    "[2] Cui, Y., Chen, Y., Liu, X., Dong, S., Tian, Y.E., Qiao, Y., Mitra, R., Han, J., Li, C., Han, X. and Liu, W., 2021. [Computational redesign of a PETase for plastic biodegradation under ambient condition by the GRAPE strategy](https://pubs.acs.org/doi/abs/10.1021/acscatal.0c05126). ACS Catalysis, 11(3), pp.1340-1350.\n",
     "\n",
-    "[3] Joo, S., Cho, I.J., Seo, H., Son, H.F., Sagong, H.Y., Shin, T.J., Choi, S.Y., Lee, S.Y. and Kim, K.J., 2018. [Structural insight into molecular mechanism of poly (ethylene terephthalate) degradation](https://www.nature.com/articles/s41467-018-02881-1). Nature communications, 9(1), p.382."
+    "[3] Liu, B., He, L., Wang, L., Li, T., Li, C., Liu, H., Luo, Y. and Bao, R., 2018. [Protein crystallography and site‐direct mutagenesis analysis of the poly (ethylene terephthalate) hydrolase PETase from Ideonella sakaiensis](https://chemistry-europe.onlinelibrary.wiley.com/doi/abs/10.1002/cbic.201800097). ChemBioChem, 19(14), pp.1471-1475.\n",
+    "\n",
+    "[4] Joo, S., Cho, I.J., Seo, H., Son, H.F., Sagong, H.Y., Shin, T.J., Choi, S.Y., Lee, S.Y. and Kim, K.J., 2018. [Structural insight into molecular mechanism of poly (ethylene terephthalate) degradation](https://www.nature.com/articles/s41467-018-02881-1). Nature communications, 9(1), p.382."
    ]
   }
  ],