de bruijn graph Search Results


de bruijn graph  (Nature Biotechnology)
90
Nature Biotechnology de bruijn graph
De Bruijn Graph, 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
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de bruijn graph - by Bioz Stars, 2026-04
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optimized iterative de bruijn graph assembly pipeline  (SourceForge net)
90
SourceForge net optimized iterative de bruijn graph assembly pipeline
A) Shotgun sequences are produced from two different genomes (shown in blue and red at the top). Those sequences are used to construct a <t>de</t> <t>Bruijn</t> graph, where nodes are formed by all possible sequences of length k-1 (in this case 4 bases), which are connected by edges of length k (5 bases). Since there are no 4mers shared between these two example genomes, the resulting de Bruijn subgraphs are separate. B) Nucleotide polymorphisms are better resolved by short kmers. We consider a mixture of four genomes, each with three polymorphic positions separated by 25 bp. The identity at each polymorphic position is represented by either blue or red to indicate different nucleotides. At all other positions the genomes are identical. The de Bruijn graph that is constructed from this mixture of genomes using a kmer of 23 is shown on the left, where three independent bubbles form around each polymorphic position. The equivalent graph at k = 27 is shown on the right, where three independent sets of bubbles overlap, forming a more complex and suboptimal graph structure. C) Short regions of similarity are better resolved by long kmers. We consider a mixture of two genomes which are entirely different except for a 25 bp region of sequence identity (shown in black). The de Bruijn graph that is constructed from this mixture at k = 23 is shown on the left, where the two resulting subgraphs intersect at the 23mer of similarity. The de Bruijn graph at k = 27 is shown on the right, where the two resulting subgraphs (corresponding to the two genomes) do not intersect, since they have no 26mer in common. The examples in B and C together illustrate how different kmers can be optimal for assembling graphs with different types of polymorphisms.
Optimized Iterative De Bruijn Graph Assembly Pipeline, supplied by SourceForge net, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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optimized iterative de bruijn graph assembly pipeline - by Bioz Stars, 2026-04
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de bruijn graph-type illumina-only assembly  (Illumina Inc)
90
Illumina Inc de bruijn graph-type illumina-only assembly
A) Shotgun sequences are produced from two different genomes (shown in blue and red at the top). Those sequences are used to construct a <t>de</t> <t>Bruijn</t> graph, where nodes are formed by all possible sequences of length k-1 (in this case 4 bases), which are connected by edges of length k (5 bases). Since there are no 4mers shared between these two example genomes, the resulting de Bruijn subgraphs are separate. B) Nucleotide polymorphisms are better resolved by short kmers. We consider a mixture of four genomes, each with three polymorphic positions separated by 25 bp. The identity at each polymorphic position is represented by either blue or red to indicate different nucleotides. At all other positions the genomes are identical. The de Bruijn graph that is constructed from this mixture of genomes using a kmer of 23 is shown on the left, where three independent bubbles form around each polymorphic position. The equivalent graph at k = 27 is shown on the right, where three independent sets of bubbles overlap, forming a more complex and suboptimal graph structure. C) Short regions of similarity are better resolved by long kmers. We consider a mixture of two genomes which are entirely different except for a 25 bp region of sequence identity (shown in black). The de Bruijn graph that is constructed from this mixture at k = 23 is shown on the left, where the two resulting subgraphs intersect at the 23mer of similarity. The de Bruijn graph at k = 27 is shown on the right, where the two resulting subgraphs (corresponding to the two genomes) do not intersect, since they have no 26mer in common. The examples in B and C together illustrate how different kmers can be optimal for assembling graphs with different types of polymorphisms.
De Bruijn Graph Type Illumina Only Assembly, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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de bruijn graph-type illumina-only assembly - by Bioz Stars, 2026-04
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de bruijn assembly graph  (Illumina Inc)
90
Illumina Inc de bruijn assembly graph
A) Shotgun sequences are produced from two different genomes (shown in blue and red at the top). Those sequences are used to construct a <t>de</t> <t>Bruijn</t> graph, where nodes are formed by all possible sequences of length k-1 (in this case 4 bases), which are connected by edges of length k (5 bases). Since there are no 4mers shared between these two example genomes, the resulting de Bruijn subgraphs are separate. B) Nucleotide polymorphisms are better resolved by short kmers. We consider a mixture of four genomes, each with three polymorphic positions separated by 25 bp. The identity at each polymorphic position is represented by either blue or red to indicate different nucleotides. At all other positions the genomes are identical. The de Bruijn graph that is constructed from this mixture of genomes using a kmer of 23 is shown on the left, where three independent bubbles form around each polymorphic position. The equivalent graph at k = 27 is shown on the right, where three independent sets of bubbles overlap, forming a more complex and suboptimal graph structure. C) Short regions of similarity are better resolved by long kmers. We consider a mixture of two genomes which are entirely different except for a 25 bp region of sequence identity (shown in black). The de Bruijn graph that is constructed from this mixture at k = 23 is shown on the left, where the two resulting subgraphs intersect at the 23mer of similarity. The de Bruijn graph at k = 27 is shown on the right, where the two resulting subgraphs (corresponding to the two genomes) do not intersect, since they have no 26mer in common. The examples in B and C together illustrate how different kmers can be optimal for assembling graphs with different types of polymorphisms.
De Bruijn Assembly Graph, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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de bruijn assembly graph - by Bioz Stars, 2026-04
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de-bruijn graph based short-read assembler euler-sr  (Illumina Inc)
90
Illumina Inc de-bruijn graph based short-read assembler euler-sr
A) Shotgun sequences are produced from two different genomes (shown in blue and red at the top). Those sequences are used to construct a <t>de</t> <t>Bruijn</t> graph, where nodes are formed by all possible sequences of length k-1 (in this case 4 bases), which are connected by edges of length k (5 bases). Since there are no 4mers shared between these two example genomes, the resulting de Bruijn subgraphs are separate. B) Nucleotide polymorphisms are better resolved by short kmers. We consider a mixture of four genomes, each with three polymorphic positions separated by 25 bp. The identity at each polymorphic position is represented by either blue or red to indicate different nucleotides. At all other positions the genomes are identical. The de Bruijn graph that is constructed from this mixture of genomes using a kmer of 23 is shown on the left, where three independent bubbles form around each polymorphic position. The equivalent graph at k = 27 is shown on the right, where three independent sets of bubbles overlap, forming a more complex and suboptimal graph structure. C) Short regions of similarity are better resolved by long kmers. We consider a mixture of two genomes which are entirely different except for a 25 bp region of sequence identity (shown in black). The de Bruijn graph that is constructed from this mixture at k = 23 is shown on the left, where the two resulting subgraphs intersect at the 23mer of similarity. The de Bruijn graph at k = 27 is shown on the right, where the two resulting subgraphs (corresponding to the two genomes) do not intersect, since they have no 26mer in common. The examples in B and C together illustrate how different kmers can be optimal for assembling graphs with different types of polymorphisms.
De Bruijn Graph Based Short Read Assembler Euler Sr, supplied by Illumina Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Average 90 stars, based on 1 article reviews
de-bruijn graph based short-read assembler euler-sr - by Bioz Stars, 2026-04
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clc genomic workbench, version 6.0, de bruijn graph assembler  (CLC Bio)
90
CLC Bio clc genomic workbench, version 6.0, de bruijn graph assembler
A) Shotgun sequences are produced from two different genomes (shown in blue and red at the top). Those sequences are used to construct a <t>de</t> <t>Bruijn</t> graph, where nodes are formed by all possible sequences of length k-1 (in this case 4 bases), which are connected by edges of length k (5 bases). Since there are no 4mers shared between these two example genomes, the resulting de Bruijn subgraphs are separate. B) Nucleotide polymorphisms are better resolved by short kmers. We consider a mixture of four genomes, each with three polymorphic positions separated by 25 bp. The identity at each polymorphic position is represented by either blue or red to indicate different nucleotides. At all other positions the genomes are identical. The de Bruijn graph that is constructed from this mixture of genomes using a kmer of 23 is shown on the left, where three independent bubbles form around each polymorphic position. The equivalent graph at k = 27 is shown on the right, where three independent sets of bubbles overlap, forming a more complex and suboptimal graph structure. C) Short regions of similarity are better resolved by long kmers. We consider a mixture of two genomes which are entirely different except for a 25 bp region of sequence identity (shown in black). The de Bruijn graph that is constructed from this mixture at k = 23 is shown on the left, where the two resulting subgraphs intersect at the 23mer of similarity. The de Bruijn graph at k = 27 is shown on the right, where the two resulting subgraphs (corresponding to the two genomes) do not intersect, since they have no 26mer in common. The examples in B and C together illustrate how different kmers can be optimal for assembling graphs with different types of polymorphisms.
Clc Genomic Workbench, Version 6.0, De Bruijn Graph Assembler, supplied by CLC Bio, 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/clc genomic workbench, version 6.0, de bruijn graph assembler/product/CLC Bio
Average 90 stars, based on 1 article reviews
clc genomic workbench, version 6.0, de bruijn graph assembler - by Bioz Stars, 2026-04
90/100 stars
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de bruijn graph  (Celera)
90
Celera de bruijn graph
A) Shotgun sequences are produced from two different genomes (shown in blue and red at the top). Those sequences are used to construct a <t>de</t> <t>Bruijn</t> graph, where nodes are formed by all possible sequences of length k-1 (in this case 4 bases), which are connected by edges of length k (5 bases). Since there are no 4mers shared between these two example genomes, the resulting de Bruijn subgraphs are separate. B) Nucleotide polymorphisms are better resolved by short kmers. We consider a mixture of four genomes, each with three polymorphic positions separated by 25 bp. The identity at each polymorphic position is represented by either blue or red to indicate different nucleotides. At all other positions the genomes are identical. The de Bruijn graph that is constructed from this mixture of genomes using a kmer of 23 is shown on the left, where three independent bubbles form around each polymorphic position. The equivalent graph at k = 27 is shown on the right, where three independent sets of bubbles overlap, forming a more complex and suboptimal graph structure. C) Short regions of similarity are better resolved by long kmers. We consider a mixture of two genomes which are entirely different except for a 25 bp region of sequence identity (shown in black). The de Bruijn graph that is constructed from this mixture at k = 23 is shown on the left, where the two resulting subgraphs intersect at the 23mer of similarity. The de Bruijn graph at k = 27 is shown on the right, where the two resulting subgraphs (corresponding to the two genomes) do not intersect, since they have no 26mer in common. The examples in B and C together illustrate how different kmers can be optimal for assembling graphs with different types of polymorphisms.
De Bruijn Graph, supplied by Celera, 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/product/Celera
Average 90 stars, based on 1 article reviews
de bruijn graph - by Bioz Stars, 2026-04
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de bruijn graph-based de novo assembler  (CLC Bio)
90
CLC Bio de bruijn graph-based de novo assembler
A) Shotgun sequences are produced from two different genomes (shown in blue and red at the top). Those sequences are used to construct a <t>de</t> <t>Bruijn</t> graph, where nodes are formed by all possible sequences of length k-1 (in this case 4 bases), which are connected by edges of length k (5 bases). Since there are no 4mers shared between these two example genomes, the resulting de Bruijn subgraphs are separate. B) Nucleotide polymorphisms are better resolved by short kmers. We consider a mixture of four genomes, each with three polymorphic positions separated by 25 bp. The identity at each polymorphic position is represented by either blue or red to indicate different nucleotides. At all other positions the genomes are identical. The de Bruijn graph that is constructed from this mixture of genomes using a kmer of 23 is shown on the left, where three independent bubbles form around each polymorphic position. The equivalent graph at k = 27 is shown on the right, where three independent sets of bubbles overlap, forming a more complex and suboptimal graph structure. C) Short regions of similarity are better resolved by long kmers. We consider a mixture of two genomes which are entirely different except for a 25 bp region of sequence identity (shown in black). The de Bruijn graph that is constructed from this mixture at k = 23 is shown on the left, where the two resulting subgraphs intersect at the 23mer of similarity. The de Bruijn graph at k = 27 is shown on the right, where the two resulting subgraphs (corresponding to the two genomes) do not intersect, since they have no 26mer in common. The examples in B and C together illustrate how different kmers can be optimal for assembling graphs with different types of polymorphisms.
De Bruijn Graph Based De Novo Assembler, supplied by CLC Bio, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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de bruijn graph-based de novo assembler - by Bioz Stars, 2026-04
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de bruijn graph  (Baier labs)
90
Baier labs de bruijn graph
A) Shotgun sequences are produced from two different genomes (shown in blue and red at the top). Those sequences are used to construct a <t>de</t> <t>Bruijn</t> graph, where nodes are formed by all possible sequences of length k-1 (in this case 4 bases), which are connected by edges of length k (5 bases). Since there are no 4mers shared between these two example genomes, the resulting de Bruijn subgraphs are separate. B) Nucleotide polymorphisms are better resolved by short kmers. We consider a mixture of four genomes, each with three polymorphic positions separated by 25 bp. The identity at each polymorphic position is represented by either blue or red to indicate different nucleotides. At all other positions the genomes are identical. The de Bruijn graph that is constructed from this mixture of genomes using a kmer of 23 is shown on the left, where three independent bubbles form around each polymorphic position. The equivalent graph at k = 27 is shown on the right, where three independent sets of bubbles overlap, forming a more complex and suboptimal graph structure. C) Short regions of similarity are better resolved by long kmers. We consider a mixture of two genomes which are entirely different except for a 25 bp region of sequence identity (shown in black). The de Bruijn graph that is constructed from this mixture at k = 23 is shown on the left, where the two resulting subgraphs intersect at the 23mer of similarity. The de Bruijn graph at k = 27 is shown on the right, where the two resulting subgraphs (corresponding to the two genomes) do not intersect, since they have no 26mer in common. The examples in B and C together illustrate how different kmers can be optimal for assembling graphs with different types of polymorphisms.
De Bruijn Graph, supplied by Baier labs, 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/product/Baier labs
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de bruijn graph - by Bioz Stars, 2026-04
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de bruijn graph  (Illumina Inc)
90
Illumina Inc de bruijn graph
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
De Bruijn Graph, supplied by Illumina Inc, 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/product/Illumina Inc
Average 90 stars, based on 1 article reviews
de bruijn graph - by Bioz Stars, 2026-04
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de bruijn graph assembler  (Celera)
90
Celera de bruijn graph assembler
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
De Bruijn Graph Assembler, supplied by Celera, 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 assembler/product/Celera
Average 90 stars, based on 1 article reviews
de bruijn graph assembler - by Bioz Stars, 2026-04
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de bruijn graph based assemblers  (Solex LLC)
90
Solex LLC de bruijn graph based assemblers
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
De Bruijn Graph Based Assemblers, supplied by Solex LLC, 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 based assemblers/product/Solex LLC
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Image Search Results


A) Shotgun sequences are produced from two different genomes (shown in blue and red at the top). Those sequences are used to construct a de Bruijn graph, where nodes are formed by all possible sequences of length k-1 (in this case 4 bases), which are connected by edges of length k (5 bases). Since there are no 4mers shared between these two example genomes, the resulting de Bruijn subgraphs are separate. B) Nucleotide polymorphisms are better resolved by short kmers. We consider a mixture of four genomes, each with three polymorphic positions separated by 25 bp. The identity at each polymorphic position is represented by either blue or red to indicate different nucleotides. At all other positions the genomes are identical. The de Bruijn graph that is constructed from this mixture of genomes using a kmer of 23 is shown on the left, where three independent bubbles form around each polymorphic position. The equivalent graph at k = 27 is shown on the right, where three independent sets of bubbles overlap, forming a more complex and suboptimal graph structure. C) Short regions of similarity are better resolved by long kmers. We consider a mixture of two genomes which are entirely different except for a 25 bp region of sequence identity (shown in black). The de Bruijn graph that is constructed from this mixture at k = 23 is shown on the left, where the two resulting subgraphs intersect at the 23mer of similarity. The de Bruijn graph at k = 27 is shown on the right, where the two resulting subgraphs (corresponding to the two genomes) do not intersect, since they have no 26mer in common. The examples in B and C together illustrate how different kmers can be optimal for assembling graphs with different types of polymorphisms.

Journal: PLoS ONE

Article Title: Conservation of Gene Cassettes among Diverse Viruses of the Human Gut

doi: 10.1371/journal.pone.0042342

Figure Lengend Snippet: A) Shotgun sequences are produced from two different genomes (shown in blue and red at the top). Those sequences are used to construct a de Bruijn graph, where nodes are formed by all possible sequences of length k-1 (in this case 4 bases), which are connected by edges of length k (5 bases). Since there are no 4mers shared between these two example genomes, the resulting de Bruijn subgraphs are separate. B) Nucleotide polymorphisms are better resolved by short kmers. We consider a mixture of four genomes, each with three polymorphic positions separated by 25 bp. The identity at each polymorphic position is represented by either blue or red to indicate different nucleotides. At all other positions the genomes are identical. The de Bruijn graph that is constructed from this mixture of genomes using a kmer of 23 is shown on the left, where three independent bubbles form around each polymorphic position. The equivalent graph at k = 27 is shown on the right, where three independent sets of bubbles overlap, forming a more complex and suboptimal graph structure. C) Short regions of similarity are better resolved by long kmers. We consider a mixture of two genomes which are entirely different except for a 25 bp region of sequence identity (shown in black). The de Bruijn graph that is constructed from this mixture at k = 23 is shown on the left, where the two resulting subgraphs intersect at the 23mer of similarity. The de Bruijn graph at k = 27 is shown on the right, where the two resulting subgraphs (corresponding to the two genomes) do not intersect, since they have no 26mer in common. The examples in B and C together illustrate how different kmers can be optimal for assembling graphs with different types of polymorphisms.

Article Snippet: Here we first describe the basic steps of the optimized iterative de Bruijn graph assembly pipeline (available at https://sourceforge.net/projects/optitdba/ ), and then describe the implementation of each step in more detail.

Techniques: Produced, Construct, Sequencing

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