FragGeneScan statistics

info info

Citations per year


Popular tool citations

chevron_left Gene prediction Frameshift prediction chevron_right

Tool usage distribution map

Tool usage distribution map
info info

Associated diseases

Associated diseases
Want to access the full stats & trends on this tool?


FragGeneScan specifications


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




No version available



This tool is not available anymore.

Publication for FragGeneScan

FragGeneScan citations


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

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% […]


Opportunities and obstacles for deep learning in biology and medicine

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 […]


Human Microbiome Acquisition and Bioinformatic Challenges in Metagenomic Studies

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, […]


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

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 (; ) […]


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

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 […]


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

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 […]

Want to access the full list of citations?
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)

FragGeneScan reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review FragGeneScan