IsoEM statistics

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Citations per year

Number of citations per year for the bioinformatics software tool IsoEM

Tool usage distribution map

This map represents all the scientific publications referring to IsoEM per scientific context
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IsoEM specifications


Unique identifier OMICS_01278
Name IsoEM
Alternative names IsoEM2/IsoDE2, IsoEM/IsoDE
Software type Package/Module
Interface Command line interface, Graphical user interface
Restrictions to use None
Input data A set of known isoforms and a file with aligned reads.
Input format SAM + GTF
Operating system Unix/Linux, Mac OS, Windows
Programming languages Java
Computer skills Advanced
Version 2.0.0
Stability Stable
Source code URL
Maintained Yes




No version available



  • person_outline iim03001
  • person_outline Igor Mandric

Additional information

IsoEM2: IsoDE2:

Publications for IsoEM

IsoEM citations


Improved data driven likelihood factorizations for transcript abundance estimation

PMCID: 5870700
PMID: 28881996
DOI: 10.1093/bioinformatics/btx262

[…] mmunity began developing principled inference methodologies to allow accurate transcript-level quantification in the presence of multi-mapping reads. Tools such as Cufflinks (), RSEM (), mmseq () and IsoEM () provided statistical models by which transcript-level abundance estimates could be inferred. These methodologies principally rely on maximum likelihood estimation to infer the transcript abun […]


A fuzzy method for RNA Seq differential expression analysis in presence of multireads

BMC Bioinformatics
PMCID: 5123383
PMID: 28185579
DOI: 10.1186/s12859-016-1195-2

[…] to genes proportionally to the expression of uniquely mapping reads (named Rescue Method) []; some more complex techniques compute an estimation of the read counts using probabilistic models, such as IsoEM [], RSEM [], Rcount [], TEtranscript [], MMR []. These methods, starting from some assumptions on the distribution of the data, model the generation of multireads and estimate the final read cou […]


Network based bioinformatics analysis of spatio temporal RNA Seq data reveals transcriptional programs underpinning normal and aberrant retinal development

BMC Genomics
PMCID: 5009874
PMID: 27586787
DOI: 10.1186/s12864-016-2822-z

[…] nce of unique exon/exon junctions in isoforms expressed in the RNA-Seq data. After mapping the RNA-Seq reads from the three samples (E16-CE, P0-CE and P0-NE) to the Ensembl 68 transcripts and running IsoEM to estimate the FPKM values for each of the three samples, genes expressed in any of the three samples were selected. Exon-exon junctions that are unique among expressed transcripts in genes tha […]


An optimized protocol for generation and analysis of Ion Proton sequencing reads for RNA Seq

BMC Genomics
PMCID: 4880854
PMID: 27229683
DOI: 10.1186/s12864-016-2745-8

[…] scripts Per Million (TPM) [], there are two major types of gene quantification method. One is alignment-based, calculating from transcriptome alignment results such as RSEM [], BitSeq [], eXpress [], IsoEM and its variation tailor-made for Ion Torrent Data MaLTA-IsoEM [, ] or genome alignment results such as Cufflinks/Cuffdiff [], HTseq [] and MISO []; it is also important to differentiate count-b […]


Union Exon Based Approach for RNA Seq Gene Quantification: To Be or Not to Be?

PLoS One
PMCID: 4641603
PMID: 26559532
DOI: 10.1371/journal.pone.0141910

[…] ce RNA-seq has become a commonplace in molecular biology laboratories, quite a number of methods have been developed for the inference of gene and isoform abundance, including RSEM [–], Cufflinks [], IsoEM [], featureCounts [] and HTSeq []. In general, the methods for gene quantification can be largely divided into two categories: transcript-based approach (such as RSEM []) and ‘union exon’-based […]


Transcriptome analysis of Brassica napus pod using RNA Seq and identification of lipid related candidate genes

BMC Genomics
PMCID: 4619414
PMID: 26499887
DOI: 10.1186/s12864-015-2062-7

[…] S3, G1, G2, and G3) to the Brassica napus genome sequences []. Then Cufflinks was used to assembly the transcripts of each sample. In addition to Cufflinks, there are several other softwares such as IsoEM that can be used to infer isoform and gene expression levels from high-throughput transcriptome sequencing [, ], and MaLTA [] that can be used to transcriptome assembly and quantification from I […]

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IsoEM institution(s)
Department of Computer Science, Georgia State University, Atlanta, GA, USA; Computer Science and Engineering Department, University of Connecticut, Storrs, CT, USA; Immunology Department, University of Connecticut Health Center, Farmington, CT, USA
IsoEM funding source(s)
Supported in part by a GSU Molecular Basis of Disease Fellowship and NSF awards 1564899, 1564936, 1618347, and 16119110.

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