Academic literature on the topic 'Read overlap graph'

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Journal articles on the topic "Read overlap graph"

1

Baaijens, Jasmijn A., and Alexander Schönhuth. "Overlap graph-based generation of haplotigs for diploids and polyploids." Bioinformatics 35, no. 21 (2019): 4281–89. http://dx.doi.org/10.1093/bioinformatics/btz255.

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Abstract Motivation Haplotype-aware genome assembly plays an important role in genetics, medicine and various other disciplines, yet generation of haplotype-resolved de novo assemblies remains a major challenge. Beyond distinguishing between errors and true sequential variants, one needs to assign the true variants to the different genome copies. Recent work has pointed out that the enormous quantities of traditional NGS read data have been greatly underexploited in terms of haplotig computation so far, which reflects that methodology for reference independent haplotig computation has not yet
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Liu, Yuansheng, and Jinyan Li. "Hamming-shifting graph of genomic short reads: Efficient construction and its application for compression." PLOS Computational Biology 17, no. 7 (2021): e1009229. http://dx.doi.org/10.1371/journal.pcbi.1009229.

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Graphs such as de Bruijn graphs and OLC (overlap-layout-consensus) graphs have been widely adopted for the de novo assembly of genomic short reads. This work studies another important problem in the field: how graphs can be used for high-performance compression of the large-scale sequencing data. We present a novel graph definition named Hamming-Shifting graph to address this problem. The definition originates from the technological characteristics of next-generation sequencing machines, aiming to link all pairs of distinct reads that have a small Hamming distance or a small shifting offset or
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3

Dida, Firaol, and Gangman Yi. "Empirical evaluation of methods for de novo genome assembly." PeerJ Computer Science 7 (July 9, 2021): e636. http://dx.doi.org/10.7717/peerj-cs.636.

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Technologies for next-generation sequencing (NGS) have stimulated an exponential rise in high-throughput sequencing projects and resulted in the development of new read-assembly algorithms. A drastic reduction in the costs of generating short reads on the genomes of new organisms is attributable to recent advances in NGS technologies such as Ion Torrent, Illumina, and PacBio. Genome research has led to the creation of high-quality reference genomes for several organisms, and de novo assembly is a key initiative that has facilitated gene discovery and other studies. More powerful analytical alg
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McNair, Katelyn, Carol Zhou, Elizabeth A. Dinsdale, Brian Souza, and Robert A. Edwards. "PHANOTATE: a novel approach to gene identification in phage genomes." Bioinformatics 35, no. 22 (2019): 4537–42. http://dx.doi.org/10.1093/bioinformatics/btz265.

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Abstract Motivation Currently there are no tools specifically designed for annotating genes in phages. Several tools are available that have been adapted to run on phage genomes, but due to their underlying design, they are unable to capture the full complexity of phage genomes. Phages have adapted their genomes to be extremely compact, having adjacent genes that overlap and genes completely inside of other longer genes. This non-delineated genome structure makes it difficult for gene prediction using the currently available gene annotators. Here we present PHANOTATE, a novel method for gene c
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Nazarie, Fahmi W., Barbara Shih, Tim Angus, et al. "Visualization and analysis of RNA-Seq assembly graphs." Nucleic Acids Research 47, no. 14 (2019): 7262–75. http://dx.doi.org/10.1093/nar/gkz599.

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AbstractRNA-Seq is a powerful transcriptome profiling technology enabling transcript discovery and quantification. Whilst most commonly used for gene-level quantification, the data can be used for the analysis of transcript isoforms. However, when the underlying transcript assemblies are complex, current visualization approaches can be limiting, with splicing events a challenge to interpret. Here, we report on the development of a graph-based visualization method as a complementary approach to understanding transcript diversity from short-read RNA-Seq data. Following the mapping of reads to a
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6

Lin, Yu, Jeffrey Yuan, Mikhail Kolmogorov, Max W. Shen, Mark Chaisson, and Pavel A. Pevzner. "Assembly of long error-prone reads using de Bruijn graphs." Proceedings of the National Academy of Sciences 113, no. 52 (2016): E8396—E8405. http://dx.doi.org/10.1073/pnas.1604560113.

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The recent breakthroughs in assembling long error-prone reads were based on the overlap-layout-consensus (OLC) approach and did not utilize the strengths of the alternative de Bruijn graph approach to genome assembly. Moreover, these studies often assume that applications of the de Bruijn graph approach are limited to short and accurate reads and that the OLC approach is the only practical paradigm for assembling long error-prone reads. We show how to generalize de Bruijn graphs for assembling long error-prone reads and describe the ABruijn assembler, which combines the de Bruijn graph and the
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7

Beaufays, Françoise, and Eric A. Wan. "Relating Real-Time Backpropagation and Backpropagation-Through-Time: An Application of Flow Graph Interreciprocity." Neural Computation 6, no. 2 (1994): 296–306. http://dx.doi.org/10.1162/neco.1994.6.2.296.

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We show that signal flow graph theory provides a simple way to relate two popular algorithms used for adapting dynamic neural networks, real-time backpropagation and backpropagation-through-time. Starting with the flow graph for real-time backpropagation, we use a simple transposition to produce a second graph. The new graph is shown to be interreciprocal with the original and to correspond to the backpropagation-through-time algorithm. Interreciprocity provides a theoretical argument to verify that both flow graphs implement the same overall weight update.
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8

Kusuma, Wisnu Ananta, and Albert Adrianus. "Pengkontruksian Bidirected Overlap Graph untuk Perakitan Sekuens DNA." Jurnal Teknologi Informasi dan Ilmu Komputer 7, no. 2 (2020): 407. http://dx.doi.org/10.25126/jtiik.2020722070.

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<p><em>De novo DNA </em>(<em>Deoxyribonucleic Acid</em>)<em> sequence assembly</em> atau perakitan sekuens DNA secara <em>De novo </em>adalah tahapan yang sangat penting dalam analisis sekuens DNA. Tahapan ini diperlukan untuk merakit atau menyambungkan kembali fragmen-fragmen DNA (<em>reads</em>) yang dihasilkan oleh <em>Next Generation Sequencing</em> menjadi genom yang utuh. Masalah perakitan DNA ini dapat direpresentasikan sebagai masalah Shortest Common Superstring (SCS). Perakitan ini memerlukan bantuan perangk
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9

Shomorony, Ilan, Samuel H. Kim, Thomas A. Courtade, and David N. C. Tse. "Information-optimal genome assembly via sparse read-overlap graphs." Bioinformatics 32, no. 17 (2016): i494—i502. http://dx.doi.org/10.1093/bioinformatics/btw450.

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10

Best, Lisa A., Laurence D. Smith, and D. Alan Stubbs. "Perception of Linear and Nonlinear Trends: Using Slope and Curvature Information to Make Trend Discriminations." Perceptual and Motor Skills 104, no. 3 (2007): 707–21. http://dx.doi.org/10.2466/pms.104.3.707-721.

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This study investigated several factors influencing the perception of nonlinear relationships in time series graphs. To model real-world data, the graphed data represented different underlying trends and included different sample sizes and amounts of variability. Six trends (increasing and decreasing linear, exponential, asymptotic) were presented on four graph types (histogram, line graph, scatterplot, suspended bar graph). The experiment assessed how these factors affect trend discrimination, with the overall goal of judging what types of graphs lead to better discrimination. Six participant
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