1,722,413 research outputs found
cancer-evolution/Evolutionary_analysis_of_coexpression_modules: First release
No full text<p>Code matches the version of manuscript submitted to Genome Biology in April 2024.</p>
Special Issue: “Cancers across Phylogeny and Cancer Evolution”
No full textThe fields of comparative cancer research and cancer evolution touch on diverse topics in oncology and are of interest both in human as well as comparative oncology, including through the use of cancer resistant animal models to understand pro- and anti-oncogenic pathways of cancer evolution. Furthermore topics on cancer-host coevolution, transmissible cancers and roles for a range of pathogens including viruses in cancer-host interplay, are an area of increasing exploration. This Special Issue aims to collect state-of-the-art primary research studies and review articles from international experts and diverse leading groups in the field of cancers in human and across animal species to update our current understanding of cancer diversity (complexity, heterogeneity and interspecies diversity) and cancer evolution. Topics on cancers from human and animal models, cancer evolution, biomarker discovery, as well as diverse roles for viruses and other pathogens, on immunity and infection, in relation to oncology, are welcome
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
Constraints in cancer evolution
No full textNext-generation deep genome sequencing has only recently allowed us to quantitatively dissect the extent of heterogeneity within a tumour, resolving patterns of cancer evolution. Intratumour heterogeneity and natural selection contribute to resistance to anticancer therapies in the advanced setting. Recent evidence has also revealed that cancer evolution might be constrained. In this review, we discuss the origins of intratumour heterogeneity and subsequently focus on constraints imposed upon cancer evolution. The presence of (1) parallel evolution, (2) convergent evolution and (3) the biological impact of acquiring mutations in specific orders suggest that cancer evolution may be exploitable. These constraints on cancer evolution may help us identify cancer evolutionary rule books, which could eventually inform both diagnostic and therapeutic approaches to improve survival outcomes
Constraints in cancer evolution
No full textNext-generation deep genome sequencing has only recently allowed us to quantitatively dissect the extent of heterogeneity within a tumour, resolving patterns of cancer evolution. Intratumour heterogeneity and natural selection contribute to resistance to anticancer therapies in the advanced setting. Recent evidence has also revealed that cancer evolution might be constrained. In this review, we discuss the origins of intratumour heterogeneity and subsequently focus on constraints imposed upon cancer evolution. The presence of (1) parallel evolution, (2) convergent evolution and (3) the biological impact of acquiring mutations in specific orders suggest that cancer evolution may be exploitable. These constraints on cancer evolution may help us identify cancer evolutionary rule books, which could eventually inform both diagnostic and therapeutic approaches to improve survival outcomes.</jats:p
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
The Ecology and Evolution of Cancer: The Ultra-Microevolutionary Process
No full textAlthough tumorigenesis has been accepted as an evolutionary process (20, 102), many forces may operate differently in cancers than in organisms, as they evolve at vastly different time scales. Among such forces, natural selection, here defined as differential cellular proliferation among distinct somatic cell genotypes, is particularly interesting because its action might be thwarted in multicellular organisms (20, 29). In this review, selection is analyzed in two stages of cancer evolution: Stage I is the evolution between tumors and normal tissues, and Stage II is the evolution within tumors. The Cancer Genome Atlas (TCGA) data show a low degree of convergent evolution in Stage I, where genetic changes are not extensively shared among cases. An equally important, albeit much less highlighted, discovery using TCGA data is that there is almost no net selection in cancer evolution. Both positive and negative selection are evident but they neatly cancel each other out, rendering total selection ineffective in the absence of recombination. The efficacy of selection is even lower in Stage II, where neutral (non-Darwinian) evolution is increasingly supported by high-density sampling studies (81, 123). Because natural selection is not a strong deterministic force, cancers usually evolve divergently even in similar tissue environments
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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