1,720,989 research outputs found
<i>De Novo</i> Discovery of Structured ncRNA Motifs in Genomic Sequences
No full textDe novo discovery of "motifs" capturing the commonalities among related noncoding ncRNA structured RNAs is among the most difficult problems in computational biology. This chapter outlines the challenges presented by this problem, together with some approaches towards solving them, with an emphasis on an approach based on the CMfinder CMfinder program as a case study. Applications to genomic screens for novel de novo structured ncRNA ncRNA s, including structured RNA elements in untranslated portions of protein-coding genes, are presented.</p
The analysis of RNA-Seq experiments using approximate likelihood
No full textThesis (Ph.D.)--University of Washington, 2020The analysis of mRNA transcript abundance with RNA-Seq is a central tool in molecular biology research, but often analyses fail to account for the uncertainty in these estimates, which can be significant, especially when trying to disentangle isoforms or duplicated genes. Preserving uncertainty necessitates a full probabilistic model of the all the sequencing reads which quickly becomes intractable, as experiments can consist of billions of reads. To overcome these limitations, we propose a new method of approximating the likelihood function of a sparse mixture model, using a technique we call the Polya tree transformation. We demonstrate that substituting this approximation for the real thing achieves most of the benefits with a fraction of the computational costs, leading to more accurate detection of differential transcript expression
Discovery and Applications of Bacterial Noncoding RNAs
No full textThesis (Ph.D.)--University of Washington, 2012Noncoding RNAs (ncRNAs) are functional transcripts that do not code for proteins. Many of them play indispensible roles in the cell. For example, the ribosomal RNAs make up the ribosome that is the factory for making proteins and riboswitches bind to small metabolites in the cell and regulate gene expression. Computational discovery of ncRNAs is challenging, however, because ncRNAs evolve rapidly on the nucleotide level while preserving secondary structure. In the first part of this thesis, we develop two clustering algorithms that are robust to weak sequence homology signals and are applicable on the genomic scale. We show that both algorithms can recover most known ncRNA families and as few as 5 homologous sequences are needed to predict a strong motif. In the second part of the thesis, we investigate whether secondary structure in- formation improves maximum likelihood tree inference for ncRNAs. An accurate phylogenetic tree has important biological and clinical applications: it can be used to infer the function of novel organisms and understand the evolutionary history of species. We show that using structure information, a more realistic gap model, and a maximum likelihood approach improves phylogenetic tree inference. In the third part of the thesis, we develop a method for profiling human gut microbial communities using high-throughput sequencing. Our method works on Illumina short reads and does not require assembly or taxonomic identification. We show that it can differentiate between the gut microbiota of healthy individuals at low sequencing depth, making it a cost-effective screening tool for large population studies. In the final part of the thesis, we use a standard additions experiment to examine sequencing bias and errors in Illumina HiSeq. We identify features associated with systematic errors and develop an error correction pipeline. We show that our method reduces base errors and produces better species diversity estimates
RNA Structural Alignments, Part I:Sankoff-Based Approaches for Structural Alignments
No full textSimultaneous alignment and secondary structure prediction of RNA sequences is often referred to as "RNA structural alignment." A class of the methods for structural alignment is based on the principles proposed by Sankoff more than 25 years ago. The Sankoff algorithm simultaneously folds and aligns two or more sequences. The advantage of this algorithm over those that separate the folding and alignment steps is that it makes better predictions. The disadvantage is that it is slower and requires more computer memory to run. The amount of computational resources needed to run the Sankoff algorithm is so high that it took more than a decade before the first implementation of a Sankoff style algorithm was published. However, with the faster computers available today and the improved heuristics used in the implementations the Sankoff-based methods have become practical. This chapter describes the methods based on the Sankoff algorithm. All the practical implementations of the algorithm use heuristics to make them run in reasonable time and memory. These heuristics are also described in this chapter.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Quantifying wellness and disease with personal, dense, dynamic data clouds
No full textThesis (Ph.D.)--University of Washington, 2020Precision Medicine, where medical treatment is guided by deep molecular knowledge of the individual, has gained momentum in recent years. Rapid advancement in biological measurement technologies such as genome sequencing, mass spectrometry, protein capture assays, microfluidics and quantified-self devices provide an unprecedented opportunity to quantify, explain, and affect each person's health. The key challenge now is how to utilize these new capabilities to maximize wellness and prevent disease. These developments are concurrent with and aided by the increased availability of robust data analytic tools and cheap, scalable computation. In this dissertation, I present three steps taken to advance Precision Medicine. I present the first large multi-omic wellness study, where information from these -omics were integrated and used to provide personalized wellness guidance through a trained wellness coach. I present a holistic and modifiable wellness marker based on aging, generated from longitudinal multi-omic data. Finally, I apply systems approaches with dense phenotypic longitudinal data to profiling cancer, highlighting one approach to personalized 'N of 1' medicine. The research I present in this dissertation has led to the formation of two companies, so far
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe 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
Get PDFWe 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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