Overview of the gene regulation network and the bacteria biotope tasks in BioNLP'13 shared task

Abstract

Background: We present the two Bacteria Track tasks of BioNLP 2013 Shared Task (ST): Gene Regulation Network (GRN) and Bacteria Biotope (BB). These tasks were previously introduced in the 2011 BioNLP-ST Bacteria Track as Bacteria Gene Interaction (BI) and Bacteria Biotope (BB). The Bacteria Track was motivated by a need to develop specific BioNLP tools for fine-grained event extraction in bacteria biology. The 2013 tasks expand on the 2011 version by better addressing the biological knowledge modeling needs. New evaluation metrics were designed for the new goals. Moving beyond a list of gene interactions, the goal of the GRN task is to build a gene regulation network from the extracted gene interactions. BB'13 is dedicated to the extraction of bacteria biotopes, i.e. bacterial environmental information, as was BB'11. BB'13 extends the typology of BB'11 to a large diversity of biotopes, as defined by the OntoBiotope ontology. The detection of entities and events is tackled by distinct subtasks in order to measure the progress achieved by the participant systems since 2011.

Results: This paper details the corpus preparations and the evaluation metrics, as well as summarizing and discussing the participant results. Five groups participated in each of the two tasks. The high diversity of the participant methods reflects the dynamism of the BioNLP research community.

Conclusion: The evaluation results suggest new research directions for the improvement and development of Information Extraction for molecular and environmental biology. The Bacteria Track tasks remain publicly open; the BioNLP-ST website provides an online evaluation service, the reference corpora and the evaluation tools.

Figure 1

Sketching out regulatory bacterial gene transcription molecular mechanisms. (1) The RNA polymerase must bind to a transcription factor called sigma factor, to be able to transcribe DNA to RNA. (2.a) The sigma factor specifically recognizes a transcription promoter DNA sequence motif, upstream part of the gene, and drives the RNA polymerase to it. (2.b) DNA is copied into RNA from the Transcriptional Start Site (TSS), while the sigma factor is released and available for another RNA polymerase. (3.a) A transcriptional regulator binds to a specific motif around the promoter site, and in this example (3.b) activates transcription.

Figure 2

From molecular mechanisms to biological interaction. 1) the network arc between gerE and cwlH in Ex. 3 is inferred from the Interaction:Regulation event. Since the interaction target is an event, the target is reduced to its participant (cwlH); 2) a) Bind_to and Site_of represent low-level biological phenomena from which we can deduce the Master_of_promoter relation of 2) b); c) the Interaction:Binding relation can be deduced from Master_of_Promoter and Promoter_of; 3) the combined interactions from examples 1) and 2) produce the network with 3 edges and two arcs.

Figure 3

Typology of errors in the GRN network.

Figure 4

Examples of the provided information and the expected prediction in BB'13.

Figure 5

OntoBiotope category assignment with AlvisAE annotation editor.

Figure 6

Example of two possible matches between the reference and the prediction.