1,720,969 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
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
Computational Perspectives on Complex Gene Relationships and Disease: From Cancer Networks to Gene Embeddings
No full textThe rapid proliferation of omics datasets driven by advances in high-throughput sequencing and molecular profiling has created unprecedented opportunities for understanding biological systems. However, the sheer complexity and scale of these data require computational frameworks for effective analysis and interpretation. In this thesis, we explore two complementary computational approaches centered on genes: network-based analyses of patient-specific protein-protein interaction (PPI) rewiring in cancer, and a benchmarking study comparing diverse gene embedding methods for functional gene prediction tasks.
First, using a previously developed method, Splitpea, we systematically analyze exon skipping-driven network rewiring across 7,949 samples spanning 28 cancer types from The Cancer Genome Atlas. Our analysis identifies conserved, cancer-specific, and subtype-specific splicing-induced PPI network alterations, highlighting core sets of rewired genes and revealing significant associations between extreme rewiring patterns and poor prognosis. This shows the potential of splicing-driven network disruptions as a novel framework for understanding cancer through the lens of splicing alterations.
Second, recognizing the importance of effective data representation, we benchmark 38 gene embedding methods across various functional prediction tasks involving single genes and one or more gene pairs. Our findings demonstrate that embedding performance is primarily influenced by the type of training data rather than specific computational algorithms or embedding size. Notably, biomedical literature-based embeddings consistently excel across general tasks, whereas embeddings derived from gene expression data, amino acid sequences, and protein-protein interactions show superior performance in specific functional contexts.
Collectively, these two distinct yet complementary computational perspectives enhance our understanding of gene function in health and disease, providing valuable insights for leveraging computational tools to uncover molecular mechanisms in biological research
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
Network-based Analysis of Alternative Splicing Events in Alzheimer's Disease-associated Cell Types
No full textAlternative splicing (AS) contributes to transcriptomic and proteomic diversity by processing a common pre-messenger RNA into various distinct transcript and protein isoforms. Through generation of multiple protein isoforms with distinct interaction profiles, AS contributes to functional diversity and can remodel protein-protein interactions (PPIs). Dysregulation of AS has been implicated in neurodegenerative diseases, including Alzheimer’s Disease (AD), where specific neuronal populations exhibit selective vulnerability. To investigate how cognitively and physically stimulating enriched environment (EE)— a known modulator of cognitive improvement in AD progression— affects neurons vulnerable and resistant to AD, we leverage various bioinformatics approaches to study tissue and environment dynamics at different levels of biological organization.
In this thesis, we demonstrate cell type-specific transcriptional profiles of neurons selected for their association to Alzheimer’s Disease from mice exposed to baseline, non-enriched environments (NE) as well as EE. We identify distinct, cell type-specific gene regulation in response to EE for our vulnerable cell types of interest, suggesting that EE impacts different mechanisms for each of these cells. We then compare network rewiring changes driven by alternative splicing events across AD-associated cell types using a previously developed method, Splitpea, which was originally designed for cancer patient sample analysis. We adapt the tool to use a mouse PPI reference background and to handle additional upstream differential splicing analysis tool results. As a result, we detect PPI network rewiring events in experimental conditions. By comparing the rewired networks across cell types and environment, we discover EE-associated network rewiring for both vulnerable and resistant neurons, identifying changes in protein interactions and finding distinct, vulnerable-specific and resistant-specific biological processes that confer protective advantages against Alzheimer’s Disease. Overall, our study reveals a functional landscape driven by AS events in response to cognitively and physically enriched environment at the cellular level, and provides insights to protective mechanisms in the brain that can prevent Alzheimer’s Disease pathologies
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
- …
