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FragGeneScan specifications

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Unique identifier OMICS_01484
Name FragGeneScan
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages C, Perl
Computer skills Advanced
Stability Stable
Maintained No

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Publication for FragGeneScan

FragGeneScan citations

 (102)
library_books

Taxon Function Decoupling as an Adaptive Signature of Lake Microbial Metacommunities Under a Chronic Polymetallic Pollution Gradient

2018
Front Microbiol
PMCID: 5943556
PMID: 29774016
DOI: 10.3389/fmicb.2018.00869

[…] (boisvert et al., ) assembler. secondly, to explore contig features and gene contents, contigs were submitted to the mg-rast webserver (glass et al., ) and orf prediction was conducted using the fraggenescan tool (rho et al., ). afterwards, contigs were annotated with the blat tool implemented in mg-rast against the seed database using stringent filtering parameters (1e−12 as p-value, 85% […]

library_books

Opportunities and obstacles for deep learning in biology and medicine

2018
PMCID: 5938574
PMID: 29618526
DOI: 10.1098/rsif.2017.0387

[…] classification or functional annotation from sequence data where there is ample data for training. neural networks have been applied successfully to gene annotation (e.g. orphelia [] and fraggenescan []). representations (similar to word2vec [] in nlp) for protein family classification have been introduced and classified with a skip-gram neural network []. rnns show good performance […]

library_books

Human Microbiome Acquisition and Bioinformatic Challenges in Metagenomic Studies

2018
Int J Mol Sci
PMCID: 5855605
PMID: 29382070
DOI: 10.3390/ijms19020383

[…] have been optimized to use unassembled reads for functional prediction. briefly, a functional analysis is based on genes prediction to infer their probable functions. different methods, such as fraggenescan [], metagenemark [], and glimmer-mg [], have been developed and optimized for this aim. once the genes have been identified, specific databases can be used for functional predictions, […]

library_books

Metatranscriptome Sequencing Reveals Insights into the Gene Expression and Functional Potential of Rumen Wall Bacteria

2018
Front Microbiol
PMCID: 5787071
PMID: 29410661
DOI: 10.3389/fmicb.2018.00043

[…] of 70% identity to ribosomal sequences were identified () and sequences were clustered at 97% identity (). after removal of rrna sequences, putative protein coding features were predicted using fraggenescan () and clustered at 90% identity. protein similarity search against the m5nr protein database was done with blat (). for post-processing taxonomic and functional analysis, the kegg (; ) […]

library_books

Functional Characteristics of the Flying Squirrel's Cecal Microbiota under a Leaf Based Diet, Based on Multiple Meta Omic Profiling

2018
Front Microbiol
PMCID: 5758534
PMID: 29354108
DOI: 10.3389/fmicb.2017.02622

[…] were further restricted at 45 and 65% for family- and genus-level taxonomic groups, respectively (konstantinidis et al., )., to provide functional profiles of metagenomes and metatranscriptomes, fraggenescan (rho et al., ) based on the hidden markov model was used to predict open reading frames (orfs) on putative mrna reads. the orfs were queried to identify conserved protein families […]

library_books

Photosynthetic functions of Synechococcus in the ocean microbiomes of diverse salinity and seasons

2018
PLoS One
PMCID: 5749766
PMID: 29293601
DOI: 10.1371/journal.pone.0190266

[…] metagenome reads were filtered and assembled by using megahit [] with default k-mer options. subsequently, all contigs over 1,000 bp were used to identify the proteins in the microbiome by using fraggenescan []. the predicted proteins in each sample were clustered with the proteins in 13 complete reference synechococcus. in order to analyze the various aspects, cd-hit [] clustering […]


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FragGeneScan institution(s)
School of Informatics and Computing, Indiana University, Bloomington, IN; Center for Genomics and Bioinformatics, Indiana University, Bloomington, IN, USA
FragGeneScan funding source(s)
National Institutes of Health (1R01HG004908-02); National Science Foundation (CAREER award DBI-0845685)

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