Pairagon statistics

info info

Citations per year

Number of citations per year for the bioinformatics software tool Pairagon

Tool usage distribution map

This map represents all the scientific publications referring to Pairagon per scientific context
info info

Associated diseases


Popular tool citations

chevron_left Multiple nucleotide sequence alignment chevron_right
Want to access the full stats & trends on this tool?


Pairagon specifications


Unique identifier OMICS_13789
Name Pairagon
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
License BSD 2-clause “Simplified” License
Computer skills Advanced
Version 1.1
Stability Stable
Maintained Yes




No version available


  • person_outline Michael Brent

Publication for Pairagon

Pairagon citations


ASPic GeneID: A Lightweight Pipeline for Gene Prediction and Alternative Isoforms Detection

Biomed Res Int
PMCID: 3838850
PMID: 24308000
DOI: 10.1155/2013/502827

[…] st, ASPic-GeneID_AS1 is the most specific at the BTP exon, intron and nucleotide levels. Focusing on methods using ESTs and mRNAs alignments but excluding proteins, ASPic-GeneID_AS1 is as accurate as PAIRAGON-any (49%) and 2% more accurate than Exogean (47%), indicated as the best gene finding program by the EGASP assessment, in predicting exact transcript structures. Moreover, ASPic-GeneID_AS1 ha […]


CONTRAST: a discriminative, phylogeny free approach to multiple informant de novo gene prediction

Genome Biol
PMCID: 2246271
PMID: 18096039
DOI: 10.1186/gb-2007-8-12-r269

[…] lude TWINSCAN [], N-SCAN [], SLAM [], SGP [], EvoGene [], ExoniPhy [] and DOGFISH []. A third class of predictors make use of expression data, usually expressed sequence tag (EST) or cDNA alignments. Pairagon [], N-SCAN_EST [], GenomeWise [] and EXOGEAN [] belong in this category. These methods can provide highly accurate predictions for genes that are well covered by alignments of expressed seque […]


AceView: a comprehensive cDNA supported gene and transcripts annotation

Genome Biol
PMCID: 1810549
PMID: 16925834
DOI: 10.1186/gb-2006-7-s1-s12

[…] may reach up to 8% in sensitivity and 13% in specificity, between our mRNA comparisons (Table 6 in []; see Additional data file 2.1). Methods that show an advantage in [] include Ensembl, Exogean and Pairagon, and methods that show a disadvantage include AceView, ECgene, SGP2 and eight others. Yet, the general ordering of the methods is consistent across the two evaluations.On 14 December 2005, we […]


EGASP: the human ENCODE Genome Annotation Assessment Project

Genome Biol
PMCID: 1810551
PMID: 16925836
DOI: 10.1186/gb-2006-7-s1-s2

[…] ction methods are able to predict multiple transcripts per gene locus. These include four expressed sequence methods from category 3 (PAIRAGON+NSCAN_EST, EXOGEAN, ACEVIEW, and ENSEMBL), FGENESH++ and PAIRAGON-any from category 1, and MARS from category 4.Most of the methods predict genes that, on average, have fewer coding exons per gene than the GENCODE annotation (Figure ). The only exceptions t […]


Pairagon+N SCAN_EST: a model based gene annotation pipeline

Genome Biol
PMCID: 1810554
PMID: 16925839
DOI: 10.1186/gb-2006-7-s1-s5
call_split See protocol

[…] The state diagram of Pairagon's pairHMM model for cDNA-to-genome alignment is given in Figure . The different states model different alignment columns as follows: matches and mismatches are modeled by state A; intron is m […]


Using ESTs to improve the accuracy of de novo gene prediction

BMC Bioinformatics
PMCID: 1534067
PMID: 16817966
DOI: 10.1186/1471-2105-7-327

[…] s the set of available full length cDNAs. For example, we recently built a system in which the first stage is aligning full-ORF cDNA sequences to their native locus using our new cDNA-genome aligner, Pairagon []. The CDS GenBank annotations of the cDNA sequences were used to convert these alignments into gene structures. Where there is no full-length cDNA to align, we used N-SCAN_EST together with […]

Want to access the full list of citations?
Pairagon institution(s)
Department of Computer Science and Center for Genome Sciences, Washington University, St Louis, MO, USA; European Molecular Biology Laboratory, Heidelberg, Germany
Pairagon funding source(s)
This work was supported by the National Genome Research Institute under ENCODE Project (grant n°U54 HG004555) and the modENCODE Project (grant n°U01 HG004271).

Pairagon reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review Pairagon