Gene diversity in grevillea populations introduced in Brazil and its implication on management of genetic resources.

A variabilidade isoenzimática para seis populações de Grevillea robusta, oriundas de um teste de procedências/progenies, implantado no delineamento em blocos casualizados com 5 plantas por parcela, no Sul do Brasil, é descrita. A estrutura genética da população foi analisada utilizando-se marcadores bioquímicos, aos 5 anos de idade, especificamente para os locos MDH-3, PGM-2, DIA-2, PO-1, PO-2, SOD-1, e SKDH-1. As procedências do norte de ocorrência natural (Rathdowney e Woodenbong) apresentaram divergência genética superior, em relação à média das progênies, considerando o número de alelos por locus, (Ap), a riqueza alélica (Rs), a diversidade genética de Nei (H), e o coeficiente de endogamia (f). A endogamia foi detectada em diversos graus. A testemunha comercial apresentou o maior coeficiente de endogamia, (f = 0,4448), comparativamente à média das procedências (f = 0,2306), possivelmente devido à insuficiente amostragem populacional na região de origem (Austrália). Apesar de sua ocorrência natural restrita, observou-se correlação positiva entre divergência genética e distância geográfica entre as populações originais. A distância genética e análise de cluster, baseada no modelo bayesiano, mostrou três grupos de procedências distintos: 1) Rathdowney- QLD e Woodenbong-QLD; 2) Paddy?s Flat-NSW; e 3) Mann River-NSW, Boyd River-NSW e a testemunha comercial (material utilizado no Brasil). O agrupamento da testemunha com as procedências Mann River-NSW e Boyd River-NSW sugere um maior potencial das procedências do norte para o melhoramento genético visando à produção de madeira no Brasil, devido a sua elevada diversidade genética e baixo coeficiente de endogamia

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

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