1,720,962 research outputs found
RNA修飾部位を予測するための深層学習と機械学習戦略に関する研究
Full text link九州工業大学博士（情報工学）1 Introduction| 2 Methods and Materials| 3 Stack-DHUpred| 4 Meta-2OM| 5 GAPred-ac4C| 6 Conclusion| 7 Future Directions| 8 Acknowledgements| 9 List of PublicationsRNA modifications play critical roles in regulating RNA stability, structure, and function, influencing various biological processes. Among nearly 300 known chemical modifications, dihydrouridine (DHU or D) is commonly found in tRNA, mRNA, and snoRNA, which are closely associated with disease pathogenesis and various biological processes in eukaryotes. 2¢-O-methylation (2-OM or Nm) is another widespread RNA modification observed in various RNA types like tRNA, mRNA, rRNA, miRNA, piRNA, and snRNA, which occurs on the ribose sugar of RNA and contributes to stability and translational control. N4-acetylcytidine (ac4C) is another novel and highly conserved chemical modification observed in both eukaryotic and prokaryotic tRNA, rRNA, and mRNA, that is involved in maintaining translational fidelity and enhancing mRNA stability. Understanding these modifications is essential for elucidating post-transcriptional gene regulation and its potential implications in human health and disease. To comprehend its modification mechanisms and potential epigenetic regulation, it is necessary to accurately identify the modification (DHU, 2-OM, ac4C) sites.
Traditional experimental methods for detecting RNA modifications, including DHU, 2-OM, and ac4C, have significantly advanced our understanding of RNA biology. However, these methods are often labor-intensive, technically demanding, time-consuming, and costly, particularly when aiming for single-nucleotide resolution across large transcriptomes. Given these challenges, there is a growing demand for computational prediction models to complement and accelerate the discovery of RNA modification sites. Despite progress, existing computational approaches still face several limitations in prediction performance. For instance, DHU site predictors often suffer from data redundancy due to duplicate samples, limited generalizability to independent datasets, and model overfitting. In the case of 2-OM, many predictors are developed using a single type of RNA (e.g., mRNA or rRNA) or target only specific nucleotide modifications (Am, Gm, Cm, or Um), and are often trained on relatively small datasets. For ac4C, current predictors show low accuracy on independent test datasets. Moreover, several machine learning methods and feature encoding strategies remain unexplored, limiting the full potential of prediction models for these RNA modifications.
To address these challenges, in this study, we proposed three cutting-edge predictors named Stack-DHUpred, Meta-2OM, and GAPred-ac4C, which can accurately identify DHU, 2-OM, and ac4C, respectively. In Stack-DHUpred, we systematically evaluated six classifiers across 11 RNA sequence features, resulting in the development of 66 baseline (single-feature) models. These baseline models were then combined using logistic regression in a stacked ensemble framework. The optimal subset of baseline models was selected to construct the final stacked model, named Stack-DHUpred. This model achieved an accuracy greater than 0.77 and an AUC above 0.87 on the independent dataset, outperforming existing tools on both training and independent datasets. Meta-2OM utilized a meta-learning approach that considered eight conventional machine learning algorithms and eighteen different feature encoding algorithms that cover physicochemical, compositional, position-specific, and natural language processing information. The predicted probabilities of 2-OM sites from the 144 baseline models are then combined and trained using logistic regression to generate the optimal prediction. On the independent test set, Meta-2OM achieved an overall accuracy above 0.87 and AUC above 0.93, demonstrating superior performance compared to the existing predictors. GAPred-ac4C was built by combining probability scores from 120 ML and DL-based single-feature models. Using forward feature selection, a genetic algorithm-based meta-model leveraging six top-performing features from CNNBiGRU, CNNBiLSTM, CNNAtt, and LGBM achieved optimal results. GAPred-ac4C presents the AUC values of 0.893 and 0.902 for training and independent datasets, respectively, which outperformed all existing state-of-the-art methods and demonstrated the superiority of the model. Therefore, the proposed approaches significantly improved the prediction performance, and we believe that these can be extended to other sequence-based function prediction problems, including enhancer prediction, peptide therapeutic function prediction, and post-translational modification sites prediction.
To facilitate its use, two user-friendly web servers and standalone programs have been developed and are freely available at http://kurata35.bio.kyutech.ac.jp/Stack-DHUpred, http://kurata35.bio.kyutech.ac.jp/Meta-2OM/, https://github.com/kuratahiroyuki/Stack- DHUpred, and https://github.com/kuratahiroyuki/Meta-2OM.九州⼯業⼤学博⼠学位論⽂ 学位記番号：情工博甲第412号 学位授与年⽉⽇: 令和7年9⽉25⽇令和7年度doctoral thesi
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
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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Author Under Sail The Imagination of Jack London, 1893-1902
No full textIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Intro -- Title Page -- Copyright Page -- Dedication -- Contents -- Acknowledgments -- Introduction -- 1. Spirit Truth -- 2. From Absorption to Theatricality and Back Again -- 3. "I Will Build a New Present" -- 4. Sons as Authors -- 5. Fathers as Publishers -- 6. The Daughter as Author -- 7. Lovers as Authors -- 8. At Sea with the Family -- 9. Yellow News, Yellow Stories -- 10. The Return Home -- Notes -- Bibliography -- Index -- About Jay WilliamsIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Description based on publisher supplied metadata and other sources.Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, YYYY. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
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