1,721,024 research outputs found

    iBench: A ground truth approach for advanced validation of mass spectrometry identification method

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    Abstract: The discovery of many noncanonical peptides detectable with sensitive mass spectrometry inside, outside, and on cells shepherded the development of novel methods for their identification, often not supported by a systematic benchmarking with other methods. We here propose iBench, a bioinformatic tool that can construct ground truth proteomics datasets and cognate databases, thereby generating a training court wherein methods, search engines, and proteomics strategies can be tested, and their performances estimated by the same tool. iBench can be coupled to the main database search engines, allows the selection of customized features of mass spectrometry spectra and peptides, provides standard benchmarking outputs, and is open source. The proof‐of‐concept application to tryptic proteome digestions, immunopeptidomes, and synthetic peptide libraries dissected the impact that noncanonical peptides could have on the identification of canonical peptides by Mascot search with rescoring via Percolator (Mascot+Percolator)

    Proteasome isoforms in human thymi and mouse models

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    http://dx.doi.org/10.13039/501100000289 Cancer Research UKhttp://dx.doi.org/10.13039/100012470 European Organization for Nuclear Researchhttp://dx.doi.org/10.13039/100010663 European Research Counci

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    inSPIRE: An open-source tool for increased mass spectrometry identification rates using Prosit spectral prediction

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    Rescoring of mass spectrometry (MS) search results using spectral predictors can strongly increase Peptide Spectrum Match (PSM) identification rates. This approach is particularly effective when aiming to search MS data against large databases, for example when dealing with non-specific cleavage in immunopeptidomics or inflation of the reference database for noncanonical peptide identification. Here, we present inSPIRE (in silico Spectral Predictor Informed REscoring), a flexible and performant open-source rescoring pipeline built on Prosit MS spectral prediction, which is compatible with common database search engines. inSPIRE allows large scale rescoring with data from multiple MS search files, increases sensitivity to minor differences in amino acid residue position, and can be applied to various MS sample types, including tryptic proteome digestions and immunopeptidomes. inSPIRE boosts PSM identification rates in immunopeptidomics, leading to better performance than the original Prosit rescoring pipeline, as confirmed by benchmarking of inSPIRE performance on ground truth datasets. The integration of various features in the inSPIRE backbone further boosts the PSM identification in immunopeptidomics, with a potential benefit for the identification of noncanonical peptides

    Database search engines and target database features impinge upon the identification of post‐translationally cis‐spliced peptides in HLA class I immunopeptidomes

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    Unconventional epitopes presented by HLA class I complexes are emerging targets for T cell targeted immunotherapies. Their identification by mass spectrometry (MS) required development of novel methods to cope with the large number of theoretical candidates. Methods to identify post-translationally spliced peptides led to a broad range of outcomes. We here investigated the impact of three common database search engines – that is, Mascot, Mascot+Percolator, and PEAKS DB – as final identification step, as well as the features of target database on the ability to correctly identify non-spliced and cis-spliced peptides. We used ground truth datasets measured by MS to benchmark methods’ performance and extended the analysis to HLA class I immunopeptidomes. PEAKS DB showed better precision and recall of cis-spliced peptides and larger number of identified peptides in HLA class I immunopeptidomes than the other search engine strategies. The better performance of PEAKS DB appears to result from better discrimination between target and decoy hits and hence a more robust FDR estimation, and seems independent to peptide and spectrum features here investigated

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    An automated workflow to address proteome complexity and the large search space problem in proteomics and HLA-I immunopeptidomics

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    Antigenic noncanonical epitope and novel protein discovery are research areas with therapeutical applications, predominantly done via mass spectrometry. The latter should rely on a well-characterized proteogenomic search space. Its size is barely known for antigenic noncanonical peptides and novel proteins, and this could impact on their identification.To address these issues, we here develop an automated workflow comprised of Sequoia for the creation of RNA sequencing informed and exhaustive sequence search spaces for various noncanonical peptide origins, and SPIsnake for pre-filtering and exploration of sequence search space prior to mass spectrometry searches. We apply our workflow to characterize the exact sizes of tryptic and nonspecific peptide sequence search spaces in a variety of definitions, their reduction when using RNA expression, their inflation by post-translational modifications, and the frequency of peptide sequence multimapping to different noncanonical origins. Furthermore, we explore the application of Sequoia and SPIsnake on HLA-I immunopeptidomes, thereby rescuing sensitivity in peptide identification when confronted with inflated search spaces.Taken together, Sequoia and SPIsnake pave the way for an educated development of methods addressing large-scale exhaustive proteogenomic discovery by exposing the consequences of database size inflation and ambiguity of peptide and protein sequence identification

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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