Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Molecular response to water stress in two contrasting Mediterranean pines (Pinus pinaster and Pinus pinea)

Adaptation to water stress has determined the evolution and diversification of vascular plants. Water stress is forecasted to increase drastically in the next decades in certain regions, such as in the Mediterranean basin. Consequently, a proper knowledge of the response and adaptations to drought stress is essential for the correct management of plant genetic resources. However, most of the advances in the understanding of the molecular response to water stress have been attained in angiosperms, and are not always applicable to gymnosperms.In this work we analyse the transcriptional response of two emblematic Mediterranean pines, Pinus pinaster and Pinus pinea, which show noticeable differences in their performance under water stress. Using microarray analysis, up to 113 genes have been detected as significantly induced by drought in both species. Reliability of expression patterns has been confirmed by RT-PCR. While induced genes with similar profiles in both species can be considered as general candidate genes for the study of drought response in conifers, genes with diverging expression patterns can underpin the differences displayed by these species under water stress. Most promising candidate genes for drought stress response include genes related to carbohydrate metabolism, such as glycosyltransferases or galactosidases, sugar transporters, dehydrins and transcription factors. Additionally, differences in the molecular response to drought and polyethylene-glycol-induced water stress are also discussed. © 2013 Elsevier Masson SAS

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press