title: Integrating information retrieval with distant supervision for gene ontology annotation.
abstract: This article describes our participation of the Gene Ontology Curation task (GO task) in BioCreative IV where we participated in both subtasks: A) identification of GO evidence sentences (GOESs) for relevant genes in full-text articles and B) prediction of GO terms for relevant genes in full-text articles. For subtask A, we trained a logistic regression model to detect GOES based on annotations in the training data supplemented with more noisy negatives from an external resource. Then, a greedy approach was applied to associate genes with sentences. For subtask B, we designed two types of systems: (i) search-based systems, which predict GO terms based on existing annotations for GOESs that are of different textual granularities (i.e., full-text articles, abstracts, and sentences) using state-of-the-art information retrieval techniques (i.e., a novel application of the idea of distant supervision) and (ii) a similarity-based system, which assigns GO terms based on the distance between words in sentences and GO terms/synonyms. Our best performing system for subtask A achieves an F1 score of 0.27 based on exact match and 0.387 allowing relaxed overlap match. Our best performing system for subtask B, a search-based system, achieves an F1 score of 0.075 based on exact match and 0.301 considering hierarchical matches. Our search-based systems for subtask B significantly outperformed the similarity-based system.
  https://github.com/noname2020/Bioc.
authors.affiliation: Department of Health Sciences Research, Mayo Clinic, 200 First St SW, Rochester, MN 55905 and Department of Computer & Information Sciences, University of Delaware, 101 SMITH HALL, Newark, DE 19716, USA Department of Health Sciences Research, Mayo Clinic, 200 First St SW, Rochester, MN 55905 and Department of Computer & Information Sciences, University of Delaware, 101 SMITH HALL, Newark, DE 19716, USA.
authors.forename: Dongqing
authors.initials: D
authors.lastname: Zhu
authors.affiliation: Department of Health Sciences Research, Mayo Clinic, 200 First St SW, Rochester, MN 55905 and Department of Computer & Information Sciences, University of Delaware, 101 SMITH HALL, Newark, DE 19716, USA.
authors.forename: Dingcheng
authors.initials: D
authors.lastname: Li
authors.affiliation: Department of Health Sciences Research, Mayo Clinic, 200 First St SW, Rochester, MN 55905 and Department of Computer & Information Sciences, University of Delaware, 101 SMITH HALL, Newark, DE 19716, USA.
authors.forename: Ben
authors.initials: B
authors.lastname: Carterette
authors.affiliation: Department of Health Sciences Research, Mayo Clinic, 200 First St SW, Rochester, MN 55905 and Department of Computer & Information Sciences, University of Delaware, 101 SMITH HALL, Newark, DE 19716, USA liu.hongfang@mayo.edu.
authors.forename: Hongfang
authors.initials: H
authors.lastname: Liu
mesh_terms: D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D063990:Gene Ontology; D016247:Information Storage and Retrieval / Q000379:methods*; D058977:Molecular Sequence Annotation / Q000379:methods*