Information Extraction of Compound-Protein Interaction from Scientific Paper using Machine Learning

Aulia Afriza, Muhammas Rheza Muztahid, - Annisa, Wisnu Ananta Kusuma


Drug Target Interaction (DTI) is an important process in drug discovery that aims to identify useful compounds in treatment. DTI research is mostly found in databases and literature or papers. To obtain DTI information, another method such as information extraction is required to retrieve information related to DTI interactions. The information in the abstract of the research paper contains many compound sentences. This study performs regular expressions to identify compound sentences, text mining for information extraction, and classification using Bernoulli Naive Bayes. The research uses a collection of abstract documents, where 3.000 abstract documents will be arranged into 29.363 sentences. Sentences that the regular expression has parsed are matched using pattern matching and conducted by text pre-processing. Sentences resulting from text pre-processing stages are used as training datasets. We use 10- fold cross-validation to evaluate the model. This research obtained the best average accuracy value of 0.72 for using naive Bayes without regular expression for compound sentences and 0.76 accuracies for naive Bayes with a regular expression for single sentences. Furthermore, by applying the feature selection process for compound sentence data, we obtained an accuracy of 0.731 for the model without regular expressions and an accuracy of 0.7644 for the model with feature selection using regular expressions.


Drug target interaction; information extraction; text mining.

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X. Xia. Bioinformatics and Drug Discovery. Bentham Sciences Publishers. 2017. pp. 1709-1726.

L. Lee and H. Nam. “Identifications of Drug Target Interactions by a Random Walk with Restart Method on an Interaction Networkâ€. BMC Informatics Journal. vol. 19, no. 8, pp. 208. 2017.

R. Chen, X. Liu, S. Jin , J. Lin , and J. Liu. “Machine Learning for Drug Target Interaction Predictionâ€. Journal Molecules. vol. 23, pp. 2208. 2018.

MU. Maheswari and JGR. Sathiaseelan. “Text Mining: A survey on text mining-techniques and applicationâ€.International Journal of Science and Research (IJSR). vol. 6, pp. 1660–1664. 2017.

PY. Lung, T. Zhao, Z. He, and J. Zhang. “Extracting chemical protein interactions from literatureâ€. Florida State University. 2018.

S. Liu et al. “Attention Based Neural Network for Chemical Protein Relation Extractionâ€. University at Buffalo USA. 2017.

Y. Yamamoto, Y. Matsumoto, and T. Watanabe. “Dependency Patterns of Complex Sentences and Semantic Disambiguation for Abstract Meaning Representation Parsingâ€. in Proc, Conference on Lexical and Computational Semantics. Bangkok, Thailand. 2021. pp. 212-221

M. Cu et al. “Regular Expressions Based Medical Text Classification using Constructive Heuristic Approchâ€. in IEEE Access, vol. 7, pp. 147892-147904, 2019, doi: 10.1109/ACCESS.2019.2946622.

A. Konys. “Torwards Knowledge Handling in Ontology- Based Infromation Extraction Systemsâ€. in Procedia Computer Science. vol. 126, pp. 2208-2218. 2018.

C. Zong, R, Xia, and J. Zang. Information Extraction. In: Text Data Mining. Springer, Singapore. 2021.

J. Starvoka, M. Staraka, and J. Hajic. “Neural architectures for nested NER through Linearizationâ€. arXiv preprint arXiv:1908.06926. 2019.

M, Erin et al. “Ensemble Labeling Towards Scientific Information Extraction (ELSIE).†ICCS. 2021.

J, Savoy. “Working with Text Tools, Techniques, and Approches for Text Miningâ€. Journal of the Assocation for Information Science and Technology. vol. 69. 2017

B. Carpenter. “Lingpipe for 99.99% recall of gene mentionsâ€. Proceedings of the Second BioCreative Challenge Evaluation Workshop, BioCreative, pp. 307–309. 2007.

Z. Zhong et al. “Generating Regular Expressions from Natural Language Specifications: Are We There Yet?â€. Association for the Advancement of Artificial Intelligence. 2018.

L. G. Michael, J. Donohue, J. C. Davis, D. Lee and F. Servant, "Regexes are Hard: Decision-Making, Difficulties, and Risks in Regular Programming Expressions," 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2019, pp. 415-426, doi: 10.1109/ASE.2019.00047.

C. Darujati and AB. Gumelar. “Pemanfaatan teknik supervised untuk klasifikasi teks bahasa indonesiaâ€. Jurnal Bandung Text Mining, vol. 16, no 1, ISSN. 1858–4667. 2012.

YH. Kerner, D. Miller and Y. Yigal. “The influence of pre-processing on text classification using a bag-of-words representation.†PLoS ONE. 2020.

D. Abdelhafiz, C. Yang, R. Ammar, and S. Nabavi. “Deep convolutional neural networks for mammography: advances, challenges and applicationsâ€. BMC Bioinformatics 20. 2019.

K. Kowsari et al. “Text Classification Algorithms: A Survey.2019.

Heyong and H. Ming. “Supervised Hebb rule-based feature selection for text classificationâ€. in Information Processing & Management. vol. 56, pp. 167-191. 2019.

DM. Powers. “Evaluation: from precision, recall and f-measure to roc, informedness, markedness, and correlationâ€. International Journal of Machine Learning Technology. vol .2, pp.37-63. 2020.

L. García-Bañuelos, N. R. T. P. van Beest, M. Dumas, M. L. Rosa and W. Mertens, "Complete and Interpretable Conformance Checking of Business Processes," in IEEE Transactions on Software Engineering, vol. 44, no. 3, pp. 262-290. 2018, doi: 10.1109/TSE.2017.2668418.

Ghosh, M., Sanyal, G. An ensemble approach to stabilize the features for multi-domain sentiment analysis using supervised machine learning. J Big Data 5, 44. 2018.

Liang, L., Ma, C., Du, T. et al. Bioactivity-explorer: a web application for interactive visualization and exploration of bioactivity data. J Cheminform. 2019.

A. Cecile, JW. Janssens, and FK. Martens, Reflection on modern methods: Revisiting the area under the ROC Curve, International Journal of Epidemiology, Volume 49, Issue 4. 2020, Pages 1397–1403.

Nanda, M.A. et al. “A Comparison Study of Kernel Functions in the Support Vector Machine and Its Application for Termite Detectionâ€. 2018.



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