1,720,974 research outputs found
Identifying driver mutations in sequenced cancer genomes: Computational approaches to enable precision medicine
Full text linkHigh-throughput DNA sequencing is revolutionizing the study of cancer and enabling the measurement of the somatic mutations that drive cancer development. However, the resulting sequencing datasets are large and complex, obscuring the clinically important mutations in a background of errors, noise, and random mutations. Here, we review computational approaches to identify somatic mutations in cancer genome sequences and to distinguish the driver mutations that are responsible for cancer from random, passenger mutations. First, we describe approaches to detect somatic mutations from high-throughput DNA sequencing data, particularly for tumor samples that comprise heterogeneous populations of cells. Next, we review computational approaches that aim to predict driver mutations according to their frequency of occurrence in a cohort of samples, or according to their predicted functional impact on protein sequence or structure. Finally, we review techniques to identify recurrent combinations of somatic mutations, including approaches that examine mutations in known pathways or protein-interaction networks, as well as de novo approaches that identify combinations of mutations according to statistical patterns of mutual exclusivity. These techniques, coupled with advances in high-throughput DNA sequencing, are enabling precision medicine approaches to the diagnosis and treatment of cancer.</p
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
Quantifying and summarizing tumor phylogeny solution spaces
No full textSubmission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-08-01The student, Yuanyuan Qi, accepted the attached license on 2024-06-04 at 16:56.The student, Yuanyuan Qi, submitted this Dissertation for approval on 2024-06-04 at 17:12.This Dissertation was approved for publication on 2024-06-11 at 16:25.DSpace SAF Submission Ingestion Package generated from Vireo submission #20817 on 2025-02-04 at 21:15:40Cancer phylogenies are crucial for understanding tumor development and have significant clinical applications. However, due to the heterogeneity of cancer cells and limitations of current sequencing technologies, it is impractical to conclusively determine a single tree. Despite this, downstream analysis typically requires a single or a small number of trees per patient. As a result, cancer phylogeny inference methods that aim to enumerate all plausible trees quickly become unscalable as the number of mutations grows. Similarly, methods that attempt to sample high-likelihood phylogenies, often based on Markov Chain Monte Carlo (MCMC) techniques, exhibit biases in their sampling results. Another approach involves summarizing multiple possible trees into one or a few trees. However, these methods rely heavily on the quality of the given trees, which, as mentioned earlier, is challenging to enumerate or sample accurately. This thesis addresses these challenges from three aspects. In the first part, we delve into the challenges of cancer phylogeny inference using bulk data, more specifically, we study the hardness of enumeration and sampling of cancer phylogenies. We illustrate how the number of possible phylogenies grows exponentially. Additionally, we show that current sampling methods exhibit bias in their sampling results. Furthermore, we provide theoretical proof of the complexity of uniform sampling. This work establishes theoretical foundations for phylogeny inference from bulk data. In the second and third part, we focus on the problem of summarizing a given set of possible phylogenies with one or a few trees. In the second part, we generalize the problem of inferring a single consensus tree to inferring multiple consensus trees. We delve into the complexity of this problem and propose two methods to address it. We show that the multiple consensus tree is more capable and provides a better summary than a single consensus tree. In the third part, we explore the single consensus tree problem but under a different distance measure which provides a better resolution. We establish the NP-hardness of this problem under the specified distance measure. In the fourth part, we address the challenge by directly summarizing the solution space from bulk data with backbone trees. We introduce a novel method for inferring backbone trees, aimed at efficiently summarizing the solution space. We demonstrate that these back- bone trees offer a comparable summarization result to existing methods. Furthermore, we extend the method to expand these backbone trees into full trees. Our findings reveal that the full trees generated from this expansion process exhibit higher quality compared to current tree inference methods
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
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