A context-based ABC model for literature-based discovery

Yong Hwan Kim, Min Song

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Background In the literature-based discovery, considerable research has been done based on the ABC model developed by Swanson. ABC model hypothesizes that there is a meaningful relation between entity A extracted from document set 1 and entity C extracted from document set 2 through B entities that appear commonly in both document sets. The results of ABC model are relations among entity A, B, and C, which is referred as paths. A path allows for hypothesizing the relationship between entity A and entity C, or helps discover entity B as a new evidence for the relationship between entity A and entity C. The co-occurrence based approach of ABC model is a well-known approach to automatic hypothesis generation by creating various paths. However, the co-occurrence based ABC model has a limitation, in that biological context is not considered. It focuses only on matching of B entity which commonly appears in relation between two entities. Therefore, the paths extracted by the co-occurrence based ABC model tend to include a lot of irrelevant paths, meaning that expert verification is essential. Methods In order to overcome this limitation of the co-occurrence based ABC model, we propose a context-based approach to connecting one entity relation to another, modifying the ABC model using biological contexts. In this study, we defined four biological context elements: cell, drug, disease, and organism. Based on these biological context, we propose two extended ABC models: a context-based ABC model and a context-assignment-based ABC model. In order to measure the performance of the both proposed models, we examined the relevance of the B entities between the well-known relations “APOE–MAPT” as well as “FUS–TARDBP”. Each relation means interaction between neurodegenerative disease associated with proteins. The interaction between APOE and MAPT is known to play a crucial role in Alzheimer’s disease as APOE affects tau-mediated neurodegeneration. It has been shown that mutation in FUS and TARDBP are associated with amyotrophic lateral sclerosis(ALS), a motor neuron disease by leading to neuronal cell death. Using these two relations, we compared both of proposed models to co-occurrence based ABC model. Results The precision of B entities by co-occurrence based ABC model was 27.1% for “APOE–MAPT” and 22.1% for “FUS–TARDBP”, respectively. In context-based ABC model, precision of extracted B entities was 71.4% for “APOE–MAPT”, and 77.9% for “FUS–TARDBP”. Context-assignment based ABC model achieved 89% and 97.5% precision for the two relations, respectively. Both proposed models achieved a higher precision than co-occurrence-based ABC model.

Original languageEnglish
Article numbere0215313
JournalPloS one
Volume14
Issue number4
DOIs
Publication statusPublished - 2019 Apr

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Literature Based Discovery
Biological Models
Amyotrophic Lateral Sclerosis
Neurodegenerative Diseases
Alzheimer Disease
Cell Death
Mutation
Research
Pharmaceutical Preparations
Proteins

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

Cite this

@article{509cd99096094956853158211a104a1f,
title = "A context-based ABC model for literature-based discovery",
abstract = "Background In the literature-based discovery, considerable research has been done based on the ABC model developed by Swanson. ABC model hypothesizes that there is a meaningful relation between entity A extracted from document set 1 and entity C extracted from document set 2 through B entities that appear commonly in both document sets. The results of ABC model are relations among entity A, B, and C, which is referred as paths. A path allows for hypothesizing the relationship between entity A and entity C, or helps discover entity B as a new evidence for the relationship between entity A and entity C. The co-occurrence based approach of ABC model is a well-known approach to automatic hypothesis generation by creating various paths. However, the co-occurrence based ABC model has a limitation, in that biological context is not considered. It focuses only on matching of B entity which commonly appears in relation between two entities. Therefore, the paths extracted by the co-occurrence based ABC model tend to include a lot of irrelevant paths, meaning that expert verification is essential. Methods In order to overcome this limitation of the co-occurrence based ABC model, we propose a context-based approach to connecting one entity relation to another, modifying the ABC model using biological contexts. In this study, we defined four biological context elements: cell, drug, disease, and organism. Based on these biological context, we propose two extended ABC models: a context-based ABC model and a context-assignment-based ABC model. In order to measure the performance of the both proposed models, we examined the relevance of the B entities between the well-known relations “APOE–MAPT” as well as “FUS–TARDBP”. Each relation means interaction between neurodegenerative disease associated with proteins. The interaction between APOE and MAPT is known to play a crucial role in Alzheimer’s disease as APOE affects tau-mediated neurodegeneration. It has been shown that mutation in FUS and TARDBP are associated with amyotrophic lateral sclerosis(ALS), a motor neuron disease by leading to neuronal cell death. Using these two relations, we compared both of proposed models to co-occurrence based ABC model. Results The precision of B entities by co-occurrence based ABC model was 27.1{\%} for “APOE–MAPT” and 22.1{\%} for “FUS–TARDBP”, respectively. In context-based ABC model, precision of extracted B entities was 71.4{\%} for “APOE–MAPT”, and 77.9{\%} for “FUS–TARDBP”. Context-assignment based ABC model achieved 89{\%} and 97.5{\%} precision for the two relations, respectively. Both proposed models achieved a higher precision than co-occurrence-based ABC model.",
author = "Kim, {Yong Hwan} and Min Song",
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A context-based ABC model for literature-based discovery. / Kim, Yong Hwan; Song, Min.

In: PloS one, Vol. 14, No. 4, e0215313, 04.2019.

Research output: Contribution to journalArticle

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