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de bruijn graph representation of the mouse proteome dataset  (Nature Biotechnology)

 
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    Nature Biotechnology de bruijn graph representation of the mouse proteome dataset
    De Bruijn Graph Representation Of The Mouse Proteome Dataset, supplied by Nature Biotechnology, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/de bruijn graph representation of the mouse proteome dataset/product/Nature Biotechnology
    Average 90 stars, based on 1 article reviews
    de bruijn graph representation of the mouse proteome dataset - by Bioz Stars, 2026-04
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    Overview of the Ultraplexing approach. Long reads are generated in simple pooled sequencing runs. The Ultraplexing algorithm determines the most likely source genome for each long read by carrying out a comparison between the read and the <t>de</t> <t>Bruijn</t> graphs of the sequenced sample genomes, inferred from short-read data. Hybrid assembly of sample-specific long and short reads enables the recovery of complete bacterial genomes
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    Data set 1 was of constant 30-fold coverage. Data set 2 and 3 were of varying coverage. Data set 1 and 2 were generated with the default read length distribution of ART whereas data set 3 was generated with a customized longer read length distribution. If there are repeated k-mers in sequence or all the k-mers are isolated in the de Bruijn graph, then this read is defined as “useless” here.

    Journal: PLoS ONE

    Article Title: Evaluating de Bruijn Graph Assemblers on 454 Transcriptomic Data

    doi: 10.1371/journal.pone.0051188

    Figure Lengend Snippet: Data set 1 was of constant 30-fold coverage. Data set 2 and 3 were of varying coverage. Data set 1 and 2 were generated with the default read length distribution of ART whereas data set 3 was generated with a customized longer read length distribution. If there are repeated k-mers in sequence or all the k-mers are isolated in the de Bruijn graph, then this read is defined as “useless” here.

    Article Snippet: In this study, we conducted such an evaluation and found that those Illumina/Solexa-specialized de Bruijn graph assemblers performed well on 454 transcriptomic data.

    Techniques: Generated, Sequencing, Isolation

    Overview of the Ultraplexing approach. Long reads are generated in simple pooled sequencing runs. The Ultraplexing algorithm determines the most likely source genome for each long read by carrying out a comparison between the read and the de Bruijn graphs of the sequenced sample genomes, inferred from short-read data. Hybrid assembly of sample-specific long and short reads enables the recovery of complete bacterial genomes

    Journal: Genome Biology

    Article Title: Ultraplexing: increasing the efficiency of long-read sequencing for hybrid assembly with k -mer-based multiplexing

    doi: 10.1186/s13059-020-01974-9

    Figure Lengend Snippet: Overview of the Ultraplexing approach. Long reads are generated in simple pooled sequencing runs. The Ultraplexing algorithm determines the most likely source genome for each long read by carrying out a comparison between the read and the de Bruijn graphs of the sequenced sample genomes, inferred from short-read data. Hybrid assembly of sample-specific long and short reads enables the recovery of complete bacterial genomes

    Article Snippet: For each sample, a de Bruijn graph ( k = 19) is constructed from the sample-specific Illumina short-read data and the graph is cleaned (removal of low-coverage supernodes) with Cortex [ ].

    Techniques: Generated, Sequencing, Comparison