1,721,324 research outputs found
3D Single Molecule Localization using Micromirrors
No full textBioinformaticsBioinformaticsElectrical Engineering, Mathematics and Computer Scienc
Assessment of detection limits in viral diversity studies using 454 amplicon sequencing
No full textBackground Next-generation sequencing enables to detect sequence diversity in populations of viruses, an essential step in the development of drug mixtures to combat viral infections. The process of sequencing patient samples using bidirectional Roche 454 amplicon sequencing technology, as implemented at the Delft Diagnostic Laboratory (DDL), introduces specific errors. There are various cleaning algorithms capable of removing these errors. However, low frequency mutations may also be removed, as these are assumed to be likely errors and errors are assumed to be independently distributed throughout the sequence. We tested the performance of three algorithms, AmpliconNoise, KEC and ShoRAH on the detection of low-frequency mutations. Results Through various experiments we show that some types of errors are not independent but are direction-dependent, caused by homopolymeric regions. Such errors can occur in up to 80% of the reads. As the methods tested could not remove these errors, we developed novel algorithms (MSAR, AFKnn and AFC) to correct these specific errors. Our algorithms combine the information present in forward and reverse reads to detect direction-dependent errors. MASR, AFKnn and AFC improved the detection limit of viral sequences when applied before KEC. In our experiments we found mutations with a frequency below 1.0% could still be detected. Conclusion Bidirectional sequencing is essential for 454 sequencing to detect and remove direction-dependent errors and thereby improve the detection of low-frequency mutations.Computer Science: BioinformaticsPattern Recognition & Bioinformatics GroupElectrical Engineering, Mathematics and Computer Scienc
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
Adaptive methods of image processing
No full textElectrical Engineering, Mathematics and Computer Scienc
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
Topology of molecular networks
No full textIntelligent SystemsElectrical Engineering, Mathematics and Computer Scienc
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
Exploiting noisy and incomplete biological data for prediction and knowledge discovery
No full textIn modern molecular biology, the vast amount of experimental data enables us to obtain more comprehensive understanding of cellular activities, from transcription to metabolism. However, due to the inherent complexity of the cell and the various limitations of the measuring techniques, these data are often noisy and incomplete. Therefore, conclusions and hypotheses generated from these data are unreliable and remain partial. This poses a major challenge in molecular biology. This thesis contributes to this matter by proposing several approaches to handle noisy and incomplete biological data, in order to improve prediction accuracy and ease knowledge discovery. It is divided into two parts which address different problems. Part I is dedicated to the theoretical study of building noise-tolerant classifiers in the presence of class noise and measurement noise, i.e. when class labels or measured attribute values of biological instances are erroneous. For the class noise problem, we present three classifiers using probabilistic models to recover the true distribution of each class. In particular, our novel incorporation of the noise model in the Kernel Fisher discriminant offers improved prediction performance, especially on non-Gaussian data sets and data sets with relatively large numbers of features compared to their sample sizes. For measurement noise, we propose to integrate prior knowledge of the noise into kernel density based classifiers, using distinct kernels for individual samples, features, and feature values. The inclusion of prior knowledge is also shown to be especially beneficial in relatively under-sampled data sets. In Part II, we exploit the incomplete metabolic reaction and transcriptional regulation data, using both a network-centric and evolution-based approach. That is, we integrate metabolic networks and regulatory networks within species, and compare the integrated networks across different species. This integrated evolutionary network method not only provides a more comprehensive view of the cellular system, but also helps to generate more reliable information and hypotheses. Our alignment framework allows to automatically align the full metabolic networks of two species, taking into account all reaction arrangement possibilities and allowing small differences in otherwise similar reactions. We present a scoring function which measures pathway similarity in a comprehensive and flexible manner, hierarchically integrating all relevant and uncorrelated information sources. Using this method, we have identified fully conserved pathways and their variations at regulatory and metabolic level, discovered new pathway possibilities which are not represented in conventional databases, and generated hypotheses on the missing information using the information of its counterpart at another level and/or another species.MediamaticsElectrical Engineering, Mathematics and Computer Scienc
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