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SeqTar specifications


Unique identifier OMICS_05984
Name SeqTar
Alternative name SEQuencing-based sRNA TARget prediction
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Java
Computer skills Advanced
Stability No
Maintained No


No version available

Publication for SEQuencing-based sRNA TARget prediction

SeqTar citations


Genome wide identification and comprehensive analysis of microRNAs and phased small interfering RNAs in watermelon

BMC Genomics
PMCID: 5954288
PMID: 29764387
DOI: 10.1186/s12864-018-4457-8

[…] igh quality since most nucleotides had scores above 35 (Additional file : Figure S4). We identified targets of conserved miRNA by analyzing the obtained degradome profile of watermelon leaf using the SeqTar algorithm []. This analysis revealed 127 conserved targets for conserved miRNA families and TAS3 generated tasiARFs (Additional file : Tables S10 and S11).Some of the conserved miRNA targets ar […]


Phased secondary small interfering RNAs in Panaxnotoginseng

BMC Genomics
PMCID: 5780745
PMID: 29363419
DOI: 10.1186/s12864-017-4331-0

[…] that have low scored nucleotides (< 20). Then, the 3’ adapters in the remaining reads were removed. The unique sequences were obtained and the frequencies of the unique sequences were calculated. The SeqTar algorithm [] was used to predict miRNA complementary sites on the original transcripts of PHAS loci. For conserved miRNAs, the targets that have at least one valid read, i.e., read started at t […]


A multi omics study of the grapevine downy mildew (Plasmopara viticola) pathosystem unveils a complex protein coding and noncoding based arms race during infection

Sci Rep
PMCID: 5768699
PMID: 29335535
DOI: 10.1038/s41598-018-19158-8

[…] ession analysis of the P. viticola and V. vinifera transcriptomes were performed by using the Cufflinks pipeline as described in the supplementary note,. Targets cleaved by sRNAs were predicted using SeqTar and by combining different sets of sRNAs and transcriptomes as described in Šurbanovski et al.. A set of sRNAs of 21nt that mapped perfectly on P. viticola genome and a set of V. vinifera sRNAs […]


Small RNA profiles from Panax notoginseng roots differing in sizes reveal correlation between miR156 abundances and root biomass levels

Sci Rep
PMCID: 5573331
PMID: 28842680
DOI: 10.1038/s41598-017-09670-8

[…] inseng roots. Three TAS3 loci were identified in P. notoginseng. Seventy nine conserved targets of conserved miRNAs and TAS3 derived tasiRNAs were identified by using the degradome sequencing and the SeqTar algorithm. Eight of these 79 targets were further validated using the RLM 5′-RACE experiments. These results significantly improved our understanding of miRNA-guided gene regulatory networks in […]


Post transcriptional modulation of protein phosphatase PPP2CA and tumor suppressor PTEN by endogenous siRNA cleaved from hairpin within PTEN mRNA 3′UTR in human liver cells

Acta Pharmacol Sin
PMCID: 4933753
PMID: 27133296
DOI: 10.1038/aps.2016.18

[…] Randa and TargetScan, that have been used to identify esiRNA target sites within the conserved regions of the 3′UTR of genes. In addition, to assess the esiRNA targets at scale, StarScan, CleaveLand, SeqTar, sPARTA, PAREsnip, StarBase and sPARTA have been developed to predict esiRNA targets from degradome sequencing data,,,,,. We identified target genes of PTEN-sh-3p21, such as PPP2CA and PTEN, by […]


Comprehensive analysis of small RNA seq data reveals that combination of miRNA with its isomiRs increase the accuracy of target prediction in Arabidopsis thaliana

RNA Biol
PMCID: 4615835
PMID: 25629686
DOI: 10.1080/15476286.2014.996474

[…] (5′-end or 3′-end) of canonical miRNAs were taken. Here we considered canonical miRNAs as annotated in miRBase 18.We also compiled data of experimentally validated targets of miRNAs from miRTarBase, SeqTar, and the published literature into a data set called exp_valid_miR_target.txt. We used an in-house-developed Perl script, along with careful manual inspection, to select and analyze the final d […]


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SeqTar institution(s)
Institute of Developmental Biology and Molecular Medicine, Shanghai, China; School of Life Sciences, Fudan University, Shanghai, China; Department of Biochemistry and Molecular Biology, Oklahoma State University, Stillwater, OK, USA; School of Computer Science, Fudan University, Shanghai, China; Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, MO, USA
SeqTar funding source(s)
Supported in part by a start-up grant of Fudan University and a grant of the Science and Technology Commission of Shanghai Municipality (10ZR1403000); by NSF-EPSCOR award EPS0814361 and Oklahoma Agricultural Experiment Station; and by NSF (grant DBI-0743797) and NIH (grants R01GM086412 and RC1AR058681.

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