emiRIT: a text-mining-based resource for microRNA information

Abstract

microRNAs (miRNAs) are essential gene regulators, and their dysregulation often leads to diseases. Easy access to miRNA information is crucial for interpreting generated experimental data, connecting facts across publications and developing new hypotheses built on previous knowledge. Here, we present extracting miRNA Information from Text (emiRIT), a text-miningbased resource, which presents miRNA information mined from the literature through a user-friendly interface. We collected 149 ,233 miRNA –PubMed ID pairs from Medline between January 1997 and May 2020. emiRIT currently contains ‘miRNA –gene regulation’ (69 ,152 relations), ‘miRNA disease (cancer)’ (12 ,300 relations), ‘miRNA –biological process and pathways’ (23, 390 relations) and circulatory ‘miRNAs in extracellular locations’ (3782 relations). Biological entities and their relation to miRNAs were extracted from Medline abstracts using publicly available and in-house developed text-mining tools, and the entities were normalized to facilitate querying and integration. We built a database and an interface to store and access the integrated data, respectively. We provide an up-to-date and user-friendly resource to facilitate access to comprehensive miRNA information from the literature on a large scale, enabling users to navigate through different roles of miRNA and examine them in a context specific to their information needs. To assess our resource’s information coverage, we have conducted two case studies focusing on the target and differential expression information of miRNAs in the context of cancer and a third case study to assess the usage of emiRIT in the curation of miRNA information. Database URL: https://research.bioinformatics.udel.edu/emirit/

Identification of human gene research articles with wrongly identified nucleotide sequences

“…We then considered how problematic articles have been curated within gene knowledge bases and cited within the literature. Between 1 and 207 problematic articles were found within five gene knowledge bases that rely upon text mining ( 32 , 33 , 34 , 35 , 36 ), where knowledge bases of miR functions contained the most problematic articles (Table S3). In March 2021, the 712 problematic articles had been cited 17,183 times according to Google Scholar.…”

“…Post-publication notices linked with problematic articles were identified through PubMed and Google Scholar searches. PubMed ID’s or other publication identifiers were used as search queries of gene knowledge bases in May 2021 ( 32 , 33 , 34 , 35 , 36 ). Publication citation counts are those reported by Google Scholar in March 2021.…”

miRetrieve—an R package and web application for miRNA text mining

“…All miRNA extractions, term- and class-associations are generated directly from text without lexico-syntactic rules or stochastic models. This facilitates miRetrieve’s interpretability and allows miRetrieve to extract new miRNAs or recognize a differentiated scope of miRNA-associations independent from defined named entities, while the option to combine all analysis steps with rule-based tools such as miRSel ( 6 ), miRTex ( 7 ) and emiRIT ( 8 ) still remains.…”

“…This wealth of information has been summarized in manually curated databases such as miRTarBase ( 5 ), while tools such as fireflybio ( https://www.fireflybio.com/portal/search ), miRSel ( 6 ), miRTex ( 7 ) or emiRIT ( 8 ) help to automatically extract associations between miRNAs and genes and diseases from text. To further address the challenges above, we have designed miRetrieve.…”

Student biocuration projects as a learning environment

“…For microRNA projects the HGNC symbol of the microRNA target is used to search either miRTarBase 49 or emiRIT. 50 If no suitable articles are identified, then PubMed is searched with the HGNC symbol and key words such as microRNA (Supplementary Table S10, Extended data 46 ). Articles are only curated if there is evidence that the microRNA binds to the target mRNA that encodes for one of the prioritised proteins (usually this is provided by a reporter assay) and there is sufficient information about the species of the microRNA and mRNA used in the experiments.…”