1,721,040 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Variations on the Author
Full text link“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
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe 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
PepGM: A graphical model for taxonomic profiling of viral proteomes
No full textIn mass spectrometry based proteomics, protein homology leads to
many shared peptides within and between species. This complicates
taxonomic inference. inference. We introduce PepGM, a graphical model for taxonomic profiling of viral proteomes and metaproteomic datasets.
Using the graphical model, our approach computes statistically sound
scores for taxa based on peptide scores from a previous database
search, eliminating the need for commonly used heuristics
PepGM: A graphical model for taxonomic profiling of viral proteomes
No full textIn mass spectrometry based proteomics, protein homology leads to
many shared peptides within and between species. This complicates
taxonomic inference. inference. We introduce PepGM, a graphical model for taxonomic profiling of viral proteomes and metaproteomic datasets.
Using the graphical model, our approach computes statistically sound
scores for taxa based on peptide scores from a previous database
search, eliminating the need for commonly used heuristics. heuristics
Mistle: Metaproteomic index and spectral library search engine
No full textIntroduction:
With the introduction of accurate deep learning predictors, spectral matching applications might experience a renaissance in tandem mass spectrometry (MS/MS) driven proteomics. Deep learning models, e.g., Prosit, predict complete MS/MS spectra from peptide sequences and give the unprecedented ability to accurately predict mass spectra that may arise from any given proteome. However, the amount of spectral data is enormous when querying large search spaces, e.g., metaproteomes composed of many different species.
Current spectral library search software, such as SpectraST, is not equipped to meet run time and memory constraints imposed by such large MS/MS databases, covering several millions of peptide spectrum predictions.
Methods:
Inspired by the fragment index data structure that had been introduced with MSFragger, we implement an efficient peak matching algorithm for computing spectral similarity between query and library spectra. Mistle (Metaproteomic index and spectral library search engine) uses index partitioning and SIMD (Single instruction, multiple data) intrinsics, which greatly improves speed and memory efficiency for searching large spectral libraries. Mistle is written in C++20 and highly parallelized.
Results:
We demonstrate the efficiency of Mistle on two predicted spectral libraries for the lab-assembled microbial communities 9MM and SIHUMIx. Compared to the spectral library search engine SpectraST, Mistle shows a >10-fold runtime improvement and is also faster than msSLASH, which uses locality-sensitive hashing. Although Mistle is slower than MSFragger, Mistle‘s memory footprint is an order of magnitude smaller. Furthermore, we find evidence that the spectral matching approach to predicted libraries identifies peptides with higher precision. Mistle detects peptides not found by database search via MSFragger and in turn uncovers unnoticed false discoveries among their matches.
Conclusion:
In this study, we show that predicted spectral libraries can enhance peptide identification for metaproteomics. Mistle provides the means to efficiently search large-scale spectral libraries, highlighted for the microbiota 9MM and SIHUMIx
PepGM: A graphical model for taxonomic profiling of viral proteomes
No full textIn mass spectrometry based proteomics, protein homology leads to
many shared peptides within and between species. This complicates
taxonomic inference. inference. We introduce PepGM, a graphical model for taxonomic profiling of viral proteomes and metaproteomic datasets.
Using the graphical model, our approach computes statistically sound
scores for taxa based on peptide scores from a previous database
search, eliminating the need for commonly used heuristics
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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