ArticleMicrobial genomics2015
Shetti, a simple tool to parse, manipulate and search large datasets of sequences.
Article in Microbial genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
- Erratum issued
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Parsing and manipulating long and/or multiple protein or gene sequences can be a challenging process for experimental biologists and microbiologists lacking prior knowledge of bioinformatics and programming. Here we present a simple, easy, user-friendly and versatile tool to parse, manipulate and search within large datasets of long and multiple protein or gene sequences. The Shetti tool can be used to search for a sequence, species, protein/gene or pattern/motif. Moreover, it can also be used to construct a universal consensus or molecular signatures for proteins based on their physical characteristics. Shetti is an efficient and fast tool that can deal with large sets of long sequences efficiently. Shetti parses UniProt Knowledgebase and NCBI GenBank flat files and visualizes them as a table.
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What OpenQuestion holds
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.