Computational Isoform Expression Modeling
Computational Isoform Expression Modeling is a computational framework that quantitatively predicts or infers the expression levels of alternatively spliced transcript isoforms from high-throughput sequencing data by integrating statistical models, algorithmic inference, and genomic annotations to resolve isoform-level transcriptional activity.
37
Publications
3.6K
Citations
149
Authors
70
Institutions
Publications per year
2017–2026
12
Parents
37
RNA-Seq gene expression estimation with read mapping uncertainty
Bo Li, Victor Ruotti, Ron Stewart et al. · Bioinformatics · 2009 · 1.3K citations · Full text
Statistical inferences for isoform expression in RNA-Seq
Hui Jiang, Wing Hung Wong · Bioinformatics · 2009 · 482 citations · Full text
Evaluation and comparison of computational tools for RNA-seq isoform quantification
Chi Zhang, Baohong Zhang, Lih‐Ling Lin et al. · BMC Genomics · 2017 · 209 citations · Full text
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Tsinghua University
Beijing, China
5 h-index
9 publications
551 citations
University of Pennsylvania
Philadelphia, United States
4 h-index
21 publications
711 citations
University of California, Riverside
Riverside, United States
3 h-index
8 publications
406 citations
Houston Methodist
Houston, United States
2 h-index
5 publications
146 citations

Karolinska Institutet
Stockholm, Sweden
2 h-index
8 publications
144 citations

Chinese Academy of Sciences
Beijing, China
2 h-index
6 publications
230 citations
University of Wisconsin–Madison
Madison, United States
2 h-index
10 publications
7K citations
Morgridge Institute for Research
Madison, United States
2 h-index
12 publications
7.2K citations
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12 publications · 2.2K citations
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5 publications · 176 citations
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3 publications · 312 citations
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2 publications · 97 citations
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1 publications · 10 citations
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