Evidence map›Paper›PMID 26020441›Full record

ArticleJournal of computational biology : a journal of computational molecular cell biology2015

Reconstructing breakage fusion bridge architectures using noisy copy numbers.

Shay Zakov, Vineet Bafna

Abstract read
In one paragraph

Article in Journal of computational biology : a journal of computational molecular cell biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Shay ZakovDepartment of Computer Science and Engineering, University of California San Diego, La Jolla, California.
Vineet BafnaDepartment of Computer Science and Engineering, University of California San Diego, La Jolla, California.

Funding

Algorithmic strategies for detecting structural variation in genomesR01HG004962 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BAFNA, VINEET · 2009 to 2012
$1.3M
NHGRI NIH HHS R01-HG004962
6 · The paper itself

Abstract

The Breakage Fusion Bridge (BFB) process is a key marker for genomic instability, producing highly rearranged genomes in relatively small numbers of cell cycles. While the process itself was observed during the late 1930s, little is known about the extent of BFB in tumor genome evolution. Moreover, BFB can dramatically increase copy numbers of chromosomal segments, which in turn hardens the tasks of both reference-assisted and ab initio genome assembly. Based on available data such as Next Generation Sequencing (NGS) and Array Comparative Genomic Hybridization (aCGH) data, we show here how BFB evidence may be identified, and how to enumerate all possible evolutions of the process with respect to observed data. Specifically, we describe practical algorithms that, given a chromosomal arm segmentation and noisy segment copy number estimates, produce all segment count vectors supported by the data that can be produced by BFB, and all corresponding BFB architectures. This extends the scope of analyses described in our previous work, which produced a single count vector and architecture per instance. We apply these analyses to a comprehensive human cancer dataset, demonstrate the effectiveness and efficiency of the computation, and suggest methods for further assertions of candidate BFB samples. Source code of our tool can be found online.

Indexed as

AlgorithmsChromosomesComparative Genomic HybridizationGene AmplificationGene DosageGenome, HumanGenomic InstabilityHigh-Throughput Nucleotide SequencingHumansNeoplasmsalgorithmscombinatorial proteomicscomputational molecular biologydynamic programminggenetic variationRNAsequence analysis.

Identifiers

PMID26020441
PMCPMC4449712

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.