ReviewNucleic acids research2012
Prospects and limitations of full-text index structures in genome analysis.
Review in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
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.
Who cites it
11 citing papers in PubMed.
- Pattern Matching for DNA Sequencing Data Using Multiple Bloom Filters.BioMed research international · 2019Article
- Visual programming for next-generation sequencing data analytics.BioData mining · 2016Review
- Tailor: a computational framework for detecting non-templated tailing of small silencing RNAs.Nucleic acids research · 2015Article
- A Long Fragment Aligner called ALFALFA.BMC bioinformatics · 2015Article
- Searching and Indexing Genomic Databases via Kernelization.Frontiers in bioengineering and biotechnology · 2015Review
- Parallel continuous flow: a parallel suffix tree construction tool for whole genomes.Journal of computational biology : a journal of computational molecular cell biology · 2014Article
- Improved search heuristics find 20,000 new alignments between human and mouse genomes.Nucleic acids research · 2014Article
- A bioinformatician's guide to the forefront of suffix array construction algorithms.Briefings in bioinformatics · 2014Article
- Indexes of large genome collections on a PC.PloS one · 2014Article
- Data compression for sequencing data.Algorithms for molecular biology : AMB · 2013Article
- Compareads: comparing huge metagenomic experiments.BMC bioinformatics · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The combination of incessant advances in sequencing technology producing large amounts of data and innovative bioinformatics approaches, designed to cope with this data flood, has led to new interesting results in the life sciences. Given the magnitude of sequence data to be processed, many bioinformatics tools rely on efficient solutions to a variety of complex string problems. These solutions include fast heuristic algorithms and advanced data structures, generally referred to as index structures. Although the importance of index structures is generally known to the bioinformatics community, the design and potency of these data structures, as well as their properties and limitations, are less understood. Moreover, the last decade has seen a boom in the number of variant index structures featuring complex and diverse memory-time trade-offs. This article brings a comprehensive state-of-the-art overview of the most popular index structures and their recently developed variants. Their features, interrelationships, the trade-offs they impose, but also their practical limitations, are explained and compared.
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Registered trials
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.