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The assumption that a name uniquely identifies an entity introduces two types of errors: splitting treats one entity as two or more (because of name variants); lumping treats multiple entities as if they were one (because of shared names). Here we investigate the extent to which splitting and lumping affect commonly-used measures of large-scale named-entity networks within two disambiguated bibliographic datasets: one for co-author names in biomedicine (PubMed, 2003–2007); the other for co-inventor names in U.S. patents (USPTO, 2003–2007). In both cases, we find that splitting has relatively little effect, whereas lumping has a dramatic effect on network measures. For example, in the biomedical co-authorship network, lumping (based on last name and both initials) drives several measures down: the global clustering coefficient by a factor of 4 (from 0.265 to 0.066); degree assortativity by a factor of ∼13 (from 0.763 to 0.06); and average shortest path by a factor of 1.3 (from 5.9 to 4.5). These results can be explained in part by the fact that lumping artificially creates many intransitive relationships and high-degree vertices. This effect of lumping is much less dramatic but persists with measures that give less weight to high-degree vertices, such as the mean local clustering coefficient and log-based degree assortativity. Furthermore, the log-log distribution of collaborator counts follows a much straighter line (power law) with splitting and lumping errors than without, particularly at the low and the high counts. This suggests that part of the power law often observed for collaborator counts in science and technology reflects an artifact: name ambiguity. [ABSTRACT FROM AUTHOR]

Author attribution studies have demonstrated remarkable success in applying orthographic and lexicographic features of text in a variety of discrimination problems. What might poetic features, such as syllabic stress and mood, contribute? We address this question in the context of two different attribution problems: (a) kindred: differentiate Langston Hughes' early poems from those of kindred poets and (b) diachronic: differentiate Hughes' early from his later poems. Using a diverse set of 535 generic text features, each categorized as poetic or nonpoetic, correlation-based greedy forward search ranked the features and a support vector machine classified the poems. A small subset of features (∼10) achieved cross-validated precision and recall as high as 87%. Poetic features (rhyme patterns particularly) were nearly as effective as nonpoetic in kindred discrimination, but less effective diachronically. In other words, Hughes used both poetic and nonpoetic features in distinctive ways and his use of nonpoetic features evolved systematically while he continued to experiment with poetic features. These findings affirm qualitative studies attesting to structural elements from Black oral tradition and Black folk music (blues) and to the internal consistency of Hughes' early poetry. [ABSTRACT FROM AUTHOR]

Abstract: The Arrowsmith two-node search is a strategy that is designed to assist biomedical investigators in formulating and assessing scientific hypotheses. More generally, it allows users to identify biologically meaningful links between any two sets of articles A and C in PubMed, even when these share no articles or authors in common and represent disparate topics or disciplines. The key idea is to relate the two sets of articles via title words and phrases (B-terms) that they share. We have created a free, public web-based version of the two-node search tool (http://arrowsmith.psych.uic.edu), have described its development and implementation, and have presented analyses of individual two-node searches. In this paper, we provide an updated tutorial intended for end-users, that covers the use of the tool for a variety of potential scientific use case scenarios. For example, one can assess a recent experimental, clinical or epidemiologic finding that connects two disparate fields of inquiry—identifying likely mechanisms to explain the finding, and choosing promising follow-up lines of investigation. Alternatively, one can assess whether the existing scientific literature lends indirect support to a hypothesis posed by the user that has not yet been investigated. One can also employ two-node searches to search for novel hypotheses. Arrowsmith provides a service that cannot be carried out feasibly via standard PubMed searches or by other available text mining tools. [Copyright &y& Elsevier]

We have characterized the expression of microRNAs and selected microRNA precursors within several synaptic fractions of adult mouse forebrain, including synaptoneurosomes, synaptosomes and isolated post-synaptic densities (PSDs), using methods of microRNA microarray, real time qRT-PCR, Northern blotting and immunopurification using anti-PSD95 antibody. The majority of brain microRNAs (especially microRNAs known to be expressed in pyramidal neurons) are detectably expressed in synaptic fractions, and a subset of microRNAs is significantly enriched in synaptic fractions relative to total forebrain homogenate. MicroRNA precursors are also detectable in synaptic fractions at levels that are comparable to whole tissue. Whereas mature microRNAs are predominantly associated with soluble components of the synaptic fractions, microRNA precursors are predominantly associated with PSDs. For seven microRNAs examined, there was a significant correlation between the relative synaptic enrichment of the precursor and the relative synaptic enrichment of the corresponding mature microRNA. These findings support the proposal that microRNAs are formed, at least in part, via processing of microRNA precursors locally within dendritic spines. Dicer is expressed in PSDs but is enzymatically inactive until conditions that activate calpain cause its liberation; thus, we propose that synaptic stimulation may lead to local processing of microRNA precursors in proximity to the synapse. [ABSTRACT FROM AUTHOR]

Recently, we reported that four microRNAs show perfect complementarity with MIR/LINE-2 elements within human mRNAs. This finding raises the question of whether microRNAs might also target other genomic repeats and transposable elements. Here, we demonstrate that almost 30 human microRNAs exhibit typical short-seed complementarity with a specific site within Alu elements that is highly conserved within 3′ untranslated regions of human mRNAs. The results suggest that at least some Alu elements within human mRNAs serve as microRNA targets. [Copyright &y& Elsevier]

Arrowsmith is a unique computer-assisted strategy designed to assist investigators in detecting biologically-relevant connections between two disparate sets of articles in Medline. This paper describes how an inter-institutional consortion of neuroscientists used the UIC Arrowsmith web interface http://arrowsmith.psych.uic.edu in their daily work and guided the development, refinement and expansion of the system into a suite of tools intended for used by the wider scientific community. [ABSTRACT FROM AUTHOR]

In this article, we show that a subset of conventional mammalian microRNAs is derived from LINE-2 transposable elements and other genome repeats. These repeat-derived microRNAs arise from conventional precursor hairpins and are distinct from the rasiRNAs, which appear to be processed from long double-stranded RNA precursors. The insertion of transposable elements into new genomic sites appears to be one of the driving-forces that create new microRNAs during mammalian evolution. Two of the LINE-2-derived microRNAs exhibit perfect complementarity to a large family of mRNA and EST transcripts that contain portions of MIR and other LINE-2 elements in their 3′-untranslated regions. [Copyright &y& Elsevier]

In this article, researchers present a model for estimating the probability that a pair of author names appearing on two different articles refer to the same individual. Bio-informatics research databases have dramatically accelerated the pace of discovery in the biomedical sciences. Among these, Medline is the oldest and the best curated, and arguably it contains the most scientific information insofar as it summarizes knowledge that has been published across all biomedical fields. Medline and the most popular search interface, PubMed, have devoted a great deal of attention to the comprehensive retrieval of papers according to their subject content. Thus, each paper in Medline is indexed by hierarchical controlled-vocabulary medical subject headings, and this information is used automatically in query processing by PubMed. The model uses a simple yet powerful similarity profile between a pair of articles, based on title, journal name, coauthor names, medical subject headings, language, affiliation, and name attributes. The similarity profile distribution is computed from reference sets consisting of pairs of articles containing almost exclusively author matches versus non-matches, generated in an unbiased manner. Although the match set is generated automatically and might contain a small proportion of non-matches, the model is quite robust against contamination with non-matches.

Background: MicroRNAs are ~17-24 nt. noncoding RNAs found in all eukaryotes that degrade messenger RNAs via RNA interference (if they bind in a perfect or near-perfect complementarity to the target mRNA), or arrest translation (if the binding is imperfect). Several microRNA targets have been identified in lower organisms, but only one mammalian microRNA target has yet been validated experimentally. Results: We carried out a population-wide statistical analysis of how human microRNAs interact complementarily with human mRNAs, looking for characteristics that differ significantly as compared with scrambled control sequences. These characteristics were used to identify a set of 71 outlier mRNAs unlikely to have been hit by chance. Unlike the case in C. elegans and Drosophila, many human microRNAs exhibited long exact matches (10 or more bases in a row), up to and including perfect target complementarity. Human microRNAs hit outlier mRNAs within the protein coding region about 2/3 of the time. And, the stretches of perfect complementarity within microRNA hits onto outlier mRNAs were not biased near the 5'-end of the microRNA. In several cases, an individual microRNA hit multiple mRNAs that belonged to the same functional class. Conclusions: The analysis supports the notion that sequence complementarity is the basis by which microRNAs recognize their biological targets, but raises the possibility that human microRNA-mRNA target interactions follow different rules than have been previously characterized in Drosophila and C. elegans. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of completely reconstructing deterministic monotone Boolean functions via me membership queries. The minimum average query complexity is guaranteed via recursion, where partially ordered sets (posets) make up the overlapping subproblems. For problems with up to 4 variables, the posets' optimality conditions are summarized in the form of an evaluative criterion. The evaluative criterion extends the computational feasibility to problems involving up to about 20 variables. A framework for unbiased average case comparison of monotone Boolean function inference algorithms is developed using unequal probability sampling. The unbiased empirical results show that an implementation of the subroutine considered as a standard in the literature performs almost twice as many queries as the evaluative criterion on the average. It should also be noted that the first algorithm ever designed for this problem performed consistently within two percentage points of the evaluative criterion. As such, it prevails, by far, as the most efficient of the many preexisting algorithms. [ABSTRACT FROM AUTHOR]

Background: An article's citations are useful for finding related articles that may not be readily found by keyword searches or textual similarity. Citation analysis is also important for analyzing scientific innovation and the structure of the biomedical literature. We wanted to facilitate citation analysis for the broad community by providing a user-friendly interface for accessing and analyzing citation data for biomedical articles. Case Presentation: We seeded the Citation Cloud dataset with over 465 million open access citations culled from six different sources: PubMed Central, Microsoft Academic Graph, ArnetMiner, Semantic Scholar, Open Citations, and the NIH iCite dataset. We implemented a free, public extension to PubMed that allows any user to visualize and analyze the entire citation cloud around any paper of interest A: the set of articles cited by A, those which cite A, those which are cocited with A, and those which are bibliographically coupled to A. Conclusions: Citation Cloud greatly enables the study of citations by the scientific community, including relatively advanced analyses (co-citations and bibliographic coupling) that cannot be undertaken using other available tools. The tool can be accessed by running any PubMed query on the Anne O'Tate value-added search interface and clicking on the Citations button next to any retrieved article. [ABSTRACT FROM AUTHOR]

Abstract: Natural antisense transcripts and overlapping sense transcripts are expressed in a variety of tissues, including adult mouse brain. Here we show that a subset of mRNA-like sense–antisense transcript pairs are co-expressed within synaptoneurosomes of adult mouse forebrain, a subcellular fraction that is enriched in pinched-off dendritic spines of pyramidal neurons. Several of these pairs involve mRNAs that have been implicated in synaptic functions and in Alzheimer disease pathways. This study provides evidence that a new class of noncoding RNAs (natural antisense transcripts) are expressed near synapses, and encourages further studies of their roles in neuronal function. [Copyright &y& Elsevier]

Background: PubMed is designed to provide rapid, comprehensive retrieval of papers that discuss a given topic. However, because PubMed does not organize the search output further, it is difficult for users to grasp an overview of the retrieved literature according to non-topical dimensions, to drill-down to find individual articles relevant to a particular individual's need, or to browse the collection. Results: In this paper, we present Anne O'Tate, a web-based tool that processes articles retrieved from PubMed and displays multiple aspects of the articles to the user, according to pre-defined categories such as the "most important" words found in titles or abstracts; topics; journals; authors; publication years; and affiliations. Clicking on a given item opens a new window that displays all papers that contain that item. One can navigate by drilling down through the categories progressively, e.g., one can first restrict the articles according to author name and then restrict that subset by affiliation. Alternatively, one can expand small sets of articles to display the most closely related articles. We also implemented a novel cluster-by-topic method that generates a concise set of topics covering most of the retrieved articles. Conclusion: Anne O'Tate is an integrated, generic tool for summarization, drill-down and browsing of PubMed search results that accommodates a wide range of biomedical users and needs. It can be accessed at [4]. Peer review and editorial matters for this article were handled by Aaron Cohen. [ABSTRACT FROM AUTHOR]

Arrowsmith, a computer-assisted process for literature-based discovery, takes as input two disjoint sets of records (A, C) from the Medline database. It produces a list of title words and phrases, B, that are common to A and C, and displays the title context in which each B-term occurs within A and within C. Subject experts then can try to find A–B and B–C title-pairs that together may suggest novel and plausible indirect A–C relationships (via B-terms) that are of particular interest in the absence of any known direct A–C relationship. The list of B-terms typically is so large that it is difficult to find the relatively few that contribute to scientifically interesting connections. The purpose of the present article is to propose and test several techniques for improving the quality of the B-list. These techniques exploit the Medical Subject Headings (MeSH) that are assigned to each input record. A MesH-based concept of literature cohesiveness is defined and plays a key role. The proposed techniques are tested on a published example of indirect connections between migraine and magnesium deficiency. The tests demonstrate how the earlier results can be replicated with a more efficient and more systematic computer-aided process. [ABSTRACT FROM AUTHOR]

It was recently reported that men self-cite >50% more often than women across a wide variety of disciplines in the bibliographic database JSTOR. Here, we replicate this finding in a sample of 1.6 million papers from Author-ity, a version of PubMed with computationally disambiguated author names. More importantly, we show that the gender effect largely disappears when accounting for prior publication count in a multidimensional statistical model. Gender has the weakest effect on the probability of self-citation among an extensive set of features tested, including byline position, affiliation, ethnicity, collaboration size, time lag, subject-matter novelty, reference/citation counts, publication type, language, and venue. We find that self-citation is the hallmark of productive authors, of any gender, who cite their novel journal publications early and in similar venues, and more often cross citation-barriers such as language and indexing. As a result, papers by authors with short, disrupted, or diverse careers miss out on the initial boost in visibility gained from self-citations. Our data further suggest that this disproportionately affects women because of attrition and not because of disciplinary under-specialization. [ABSTRACT FROM AUTHOR]

Family background-kinship-can propagate careers. The evidence for academic nepotism is littered with complex associations and disputed causal inferences. Surname clustering, albeit with very careful consideration of surnames' flows across regions and time periods, can be used to reflect family ties. We examined surname patterns in the health science literature, by country, across five decades. Over 21 million papers indexed in the MEDLINE/PubMed database were analyzed. We identified relevant country-specific kinship trends over time and found that authors who are part of a kin tend to occupy central positions in their collaborative networks. Just as kin build potent academic networks with their own resources, societies may do well to provide equivalent support for talented individuals with fewer resources, on the periphery of networks. [ABSTRACT FROM AUTHOR]

Background: Recent studies suggest that alterations in expression of genes, including those which regulate neural and structural plasticity, may be crucial in the pathogenesis of depression. MicroRNAs (miRNAs) are newly discovered regulators of gene expression that have recently been implicated in a variety of human diseases, including neuropsychiatric diseases. Methodology/Principal Findings: The present study was undertaken to examine whether the miRNA network is altered in the brain of depressed suicide subjects. Expression of miRNAs was measured in prefrontal cortex (Brodmann Area 9) of antidepressant-free depressed suicide (n = 18) and well-matched non-psychiatric control subjects (n = 17) using multiplex RT-PCR plates. We found that overall miRNA expression was significantly and globally down-regulated in prefrontal cortex of depressed suicide subjects. Using individual tests of statistical significance, 21 miRNAs were significantly decreased at p = 0.05 or better. Many of the down-regulated miRNAs were encoded at nearby chromosomal loci, shared motifs within the 5'-seeds, and shared putative mRNA targets, several of which have been implicated in depression. In addition, a set of 29 miRNAs, whose expression was not pairwise correlated in the normal controls, showed a high degree of co-regulation across individuals in the depressed suicide group. Conclusions/Significance: The findings show widespread changes in miRNA expression that are likely to participate in pathogenesis of major depression and/or suicide. Further studies are needed to identify whether the miRNA changes lead to altered expression of prefrontal cortex mRNAs, either directly (by acting as miRNA targets) or indirectly (e.g., by affecting transcription factors). [ABSTRACT FROM AUTHOR]