ArticleBMC bioinformatics2010
Phylometrics: a pipeline for inferring phylogenetic trees from a sequence relationship network perspective.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed.
- Proceedings of the 2011 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) conference. Introduction.BMC bioinformatics · 2011Article
- Proceedings of the 2010 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) conference.BMC bioinformatics · 2010Article
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Authors and funding
2 authors.
Funding
Abstract
backgroundComparative sequence analysis of the 16S rRNA gene is frequently used to characterize the microbial diversity of environmental samples. However, sequence similarities do not always imply functional or evolutionary relatedness due to many factors, including unequal rates of change and convergence. Thus, relying on top BLASTN hits for phylogenetic studies may misrepresent the diversity of these constituents. Furthermore, attempts to circumvent this issue by including a large number of BLASTN hits per sequence in one tree to explore their relatedness presents other problems. For instance, the multiple sequence alignment will be poor and computationally costly if not relying on manual alignment, and it may be difficult to derive meaningful relationships from the resulting tree. Analyzing sequence relationship networks within collective BLASTN results, however, reveal sequences that are closely related despite low rank.
resultsWe have developed a web application, Phylometrics, that relies on networks of collective BLASTN results (rather than single BLASTN hits) to facilitate the process of building phylogenetic trees in an automated, high-throughput fashion while offering novel tools to find sequences that are of significant phylogenetic interest with minimal human involvement. The application, which can be installed locally in a laboratory or hosted remotely, utilizes a simple wizard-style format to guide the user through the pipeline without necessitating a background in programming. Furthermore, Phylometrics implements an independent job queuing system that enables users to continue to use the system while jobs are run with little or no degradation in performance.
conclusionsPhylometrics provides a novel data mining method to screen supplied DNA sequences and to identify sequences that are of significant phylogenetic interest using powerful analytical tools. Sequences that are identified as being similar to a number of supplied sequences may provide key insights into their functional or evolutionary relatedness. Users require the same basic computer skills as for navigating most internet applications.
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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.