Wolfgang Huber: h-index, Total Citations, and Citation Map
Wolfgang Huber's h-index is 111 (245 i10-index, 244,357+ total citations across 3+ publications) according to Google Scholar as of May 2026. Wolfgang Huber is affiliated with EMBL - European Molecular Biology Laboratory.
Wolfgang Huber is a researcher affiliated with EMBL - European Molecular Biology Laboratory, specializing in Computational Biology, Statistics, ML/AI. Their work has been cited 244,357 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Wolfgang Huber's Citation Metrics
Bibliometric impact based on 3 indexed publications.
- H-Index
- 111
- i10-Index
- 245
- Total Citations
- 244,357
- Citing Countries
- 14
As of May 2026.
Wolfgang Huber has an h-index of 111 and 244,357 total citations across 3 publications, with research cited by institutions in 14 countries.
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We've mapped 5,000 of 244,357 citations for Wolfgang Huber
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Top Cited Works
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Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
201499,777
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Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
The researcher developed a foundational statistical framework for differential expression analysis in sequence count data, establishing a standard method widely adopted across the genomics community.
The researcher developed DESeq2, a seminal statistical framework for moderated estimation of fold change and dispersion in RNA-seq data, establishing a standard for differential expression analysis.
The researcher developed HTSeq, a Python framework for high-throughput sequencing data, establishing a widely adopted standard for bioinformatics analysis.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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