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Bio-event definition in text mining towards event interconnection

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Interconnecting extracted events into reaction networks provides biologists with a wealth of fine-grained information on biochemical reactions... More specifically, we propose alignment of bio-events with the reactions in the Systems Biology Markup Language (SBML), which would make bio-events more biologically meaningful and directly re-usable by domain experts... The last decade has seen increased interest and rapid advance in the semantic study of biology, resulting in a number of semantic knowledge resources proposed by the bio community... The Systems Biology Markup Language (SBML) is a successful example of such efforts... Ohta et al. compared SBML with the event definitions in the series of GENIA tasks, pointing out that bio-event types in the current TM tasks are insufficient for covering all types of biochemical reactions in existing networks... By contrast, when we look at an SBML file, it encodes a network as a set of biochemical reactions interconnected by the participants... For example, a protein modification event in the PC task contains a single Theme... This is based on the knowledge that such events occur between proteins and certain molecules, which always result in the binding of the two... This can help event interconnections to produce more sensible reaction cascades... For example, in "post-translational modification state of CD40-associated HOIP", post-translational modification is taking place on the macromolecule consisting of CD40 and HOIP instead of either of them... Encoding extracted and inferred information from bio-events into SBML format can help by maintaining reaction directionality and enabling meaningful coreference... This position paper argues that it is possible and indeed advantageous to enhance the output formats of extracted bio-events and make them compatible with the widely used SBML format for biological reactions... The format can be further refined to meet the complexity of bio-events... A possible first step would be to use the enhanced format to annotate existing corpora, e.g. those from BioNLP tasks or adapt them to the new format semi-automatically.

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An example of Theme and cause illustrates that the directionality of event is missing.
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Figure 1: An example of Theme and cause illustrates that the directionality of event is missing.

Mentions: Consider the following two sentences annotated with BioNLP events, shown in Figure 1. The gene expression, GE1, in sentence A is a theme of a negative regulation. In sentence B, the gene expression, GE2, also is a theme of a negative regulation. However, the roles of the two gene expression (GE) events are very different, with GE1 being passively regulated in contrast to GE2, which is actually regulating another event in the sentence.


Bio-event definition in text mining towards event interconnection
An example of Theme and cause illustrates that the directionality of event is missing.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4582898&req=5

Figure 1: An example of Theme and cause illustrates that the directionality of event is missing.
Mentions: Consider the following two sentences annotated with BioNLP events, shown in Figure 1. The gene expression, GE1, in sentence A is a theme of a negative regulation. In sentence B, the gene expression, GE2, also is a theme of a negative regulation. However, the roles of the two gene expression (GE) events are very different, with GE1 being passively regulated in contrast to GE2, which is actually regulating another event in the sentence.

View Article: PubMed Central - HTML

AUTOMATICALLY GENERATED EXCERPT
Please rate it.

Interconnecting extracted events into reaction networks provides biologists with a wealth of fine-grained information on biochemical reactions... More specifically, we propose alignment of bio-events with the reactions in the Systems Biology Markup Language (SBML), which would make bio-events more biologically meaningful and directly re-usable by domain experts... The last decade has seen increased interest and rapid advance in the semantic study of biology, resulting in a number of semantic knowledge resources proposed by the bio community... The Systems Biology Markup Language (SBML) is a successful example of such efforts... Ohta et al. compared SBML with the event definitions in the series of GENIA tasks, pointing out that bio-event types in the current TM tasks are insufficient for covering all types of biochemical reactions in existing networks... By contrast, when we look at an SBML file, it encodes a network as a set of biochemical reactions interconnected by the participants... For example, a protein modification event in the PC task contains a single Theme... This is based on the knowledge that such events occur between proteins and certain molecules, which always result in the binding of the two... This can help event interconnections to produce more sensible reaction cascades... For example, in "post-translational modification state of CD40-associated HOIP", post-translational modification is taking place on the macromolecule consisting of CD40 and HOIP instead of either of them... Encoding extracted and inferred information from bio-events into SBML format can help by maintaining reaction directionality and enabling meaningful coreference... This position paper argues that it is possible and indeed advantageous to enhance the output formats of extracted bio-events and make them compatible with the widely used SBML format for biological reactions... The format can be further refined to meet the complexity of bio-events... A possible first step would be to use the enhanced format to annotate existing corpora, e.g. those from BioNLP tasks or adapt them to the new format semi-automatically.

No MeSH data available.