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

Comprehensive two-dimensional liquid chromatography: Ion chromatography × reversed-phase liquid chromatography for separation of low-molar-mass organic acids

In the work presented here a novel approach to comprehensive two-dimensional liquid chromatography is evaluated. Ion chromatography is chosen for the first-dimension separation and reversed-phase liquid chromatography is chosen for the second-dimension separation mode. The coupling of these modes is made possible by neutralising the first-dimension effluent, containing KOH, prior to transfer to the second-dimension reversed-phase column. A test mixture of 24 low-molar-mass organic acids is used for optimisation of the system. Three food and beverage samples were analysed in order to evaluate the developed methodology, the resulting two-dimensional separation is near-orthogonal, the set-up is simple and all instrumental components are available commercially. The method proved to be robust and suitable for the analysis of wine, orange juice and yogurt

Comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC x GC-TOF) for high resolution metabolomics: Biomarker discovery on spleen tissue extracts of obese NZO compared to lean C57BL/6 mice.

Comprehensive two dimensional gas chromatography – time of flight mass spectrometry (GCxGC-TOF) for high resolution metabolomics : biomarker discovery on spleen tissue extracts of obese NZO compared to lean C57BL/6 mice / R. Zimmermann ... - In: Metabolomics. 1. 2005. S. 57-6

Statistical methods for comparing comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry results: Metabolomic analysis of mouse tissue extracts.

The potential for the utilization of GC x GC-time-of-flight (TOF) MS for high-resolution metabolomics studies is discussed, with the implementation of some statistical comparisons for biomarker detection. Metabolite profiles from NZO obese mice versus BL/6 control mice are compared and contrasted using a number of chromatogram comparison routines, including direct chromatogram comparisons, chromatogram subtraction and averaging routines, as well as a method for generating relative weighted peak surface difference chromatograms, and a more conventional Student's t-test statistical approach. (c) 2005 Elsevier B.V. All rights reserved