iterations Search Results


iterative prewhitening method  (KU Leuven)
90
KU Leuven iterative prewhitening method
Iterative Prewhitening Method, supplied by KU Leuven, 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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iterative deconvolve 3d imagej plugin  (Optinav Inc)
90
Optinav Inc iterative deconvolve 3d imagej plugin
Iterative Deconvolve 3d Imagej Plugin, supplied by Optinav 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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quantum iterative reconstruction qir  (Siemens AG)
90
Siemens AG quantum iterative reconstruction qir
Quantum Iterative Reconstruction Qir, supplied by Siemens AG, 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/product/iterations/4th+generation+iterative+reconstruction+algorithm+qir/pm38641450-67-9-13
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sparse singular value decomposition (svd) methods based on power iteration  (Epigenomics ag)
90
Epigenomics ag sparse singular value decomposition (svd) methods based on power iteration
Sparse Singular Value Decomposition (Svd) Methods Based On Power Iteration, supplied by Epigenomics ag, 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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sparse singular value decomposition (svd) methods based on power iteration - by Bioz Stars, 2026-09
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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
https://www.bioz.com/product/iterations/optimized+iterative+de+bruijn+graph+assembly+pipeline/pmc03416800-133-11-18
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optimized iterative de bruijn graph assembly pipeline - by Bioz Stars, 2026-09
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iterative reconstruction with siemens somatom definition flash 128-row  (Siemens AG)
90
Siemens AG iterative reconstruction with siemens somatom definition flash 128-row
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.
Iterative Reconstruction With Siemens Somatom Definition Flash 128 Row, supplied by Siemens AG, 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/product/iterations/iterative+reconstruction+with+siemens+somatom+definition+flash+128+row/pmc05669541-219-58-63
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iterative closest point (icp) algorithm of the optocat 2010 r2  (Breuckmann GmbH)
90
Breuckmann GmbH iterative closest point (icp) algorithm of the optocat 2010 r2
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.
Iterative Closest Point (Icp) Algorithm Of The Optocat 2010 R2, supplied by Breuckmann GmbH, 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/product/iterations/iterative+closest+point++icp++algorithm+of+the+optocat+2010+r2/pmc07093666-57-18-21
Average 90 stars, based on 1 article reviews
iterative closest point (icp) algorithm of the optocat 2010 r2 - by Bioz Stars, 2026-09
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fc09 iterative reconstruction  (Canon inc)
90
Canon inc fc09 iterative reconstruction
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.
Fc09 Iterative Reconstruction, supplied by Canon 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/product/iterations/fc09+iterative+reconstruction/pmc06609439-73-14-21
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fc09 iterative reconstruction - by Bioz Stars, 2026-09
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iter core imaging x-ray spectrometer  (Neutronics Inc)
90
Neutronics Inc iter core imaging x-ray spectrometer
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.
Iter Core Imaging X Ray Spectrometer, supplied by Neutronics 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/product/iterations/iter+core+imaging+x+ray+spectrometer/10__1016_slash_j__fusengdes__2017__03__030-153-19-15
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iter core imaging x-ray spectrometer - by Bioz Stars, 2026-09
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iterative fgmres solver  (COMSOL Inc)
90
COMSOL Inc iterative fgmres solver
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.
Iterative Fgmres Solver, supplied by COMSOL 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/product/iterations/iterative+fgmres+solver/pm24320491-101-3-7
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iterative fgmres solver - by Bioz Stars, 2026-09
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sinogram-affirmed iterative reconstruction j40f [medium] kernel  (Siemens AG)
90
Siemens AG sinogram-affirmed iterative reconstruction j40f [medium] kernel
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.
Sinogram Affirmed Iterative Reconstruction J40f [Medium] Kernel, supplied by Siemens AG, 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/product/iterations/sinogram+affirmed+iterative+reconstruction+j40f++medium++kernel/pmc07963753-166-8-18
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sinogram-affirmed iterative reconstruction j40f [medium] kernel - by Bioz Stars, 2026-09
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head kernel using sinogram-affirmed iterative reconstruction  (Siemens AG)
90
Siemens AG head kernel using sinogram-affirmed iterative reconstruction
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.
Head Kernel Using Sinogram Affirmed Iterative Reconstruction, supplied by Siemens AG, 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/product/iterations/head+kernel+using+sinogram+affirmed+iterative+reconstruction++siemens++called+j30/pmc07965300-114-43-44
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head kernel using sinogram-affirmed iterative reconstruction - by Bioz Stars, 2026-09
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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