Wolfgang Huber
Impact in
- Molecular Biology top 0.01%
- RNA Research and Splicing
- RNA modifications and cancer
- Genomics and Chromatin Dynamics
- Epigenetics and DNA Methylation
- RNA and protein synthesis mechanisms
- Single-cell and spatial transcriptomics
- Cancer Research top 0.01%
- Cancer-related molecular mechanisms research
Papers in
-
- Gene expression and cancer classification 47
- RNA Research and Splicing 31
- Genomics and Chromatin Dynamics 27
- Bioinformatics and Genomic Networks 22
- Single-cell and spatial transcriptomics 17
- Molecular Biology Techniques and Applications 15
- RNA modifications and cancer 13
- Co-authors
- Simon Anders (17 shared papers)Michael I. Love (2 shared papers)Paul Theodor Pyl (5 shared papers)Robert Gentleman (22 shared papers)Steffen Durinck (2 shared papers)Ewan Birney (1 shared paper)Paul T. Spellman (1 shared paper)Annemarie Poustka (15 shared papers)
- Journals
- Bioinformatics (22 papers)Genome biology (10 papers)Blood (9 papers)Nature Methods (9 papers)Molecular Systems Biology (9 papers)
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
Wolfgang Huber
251 papers receiving 113.8k citations
Wolfgang Huber's Hit Papers
Peers
Comparison fields: 5 of 230
- Molecular Biology 62.6k
- Cancer Research 12.4k
- Aging 1.4k
- Immunology 11.6k
- Plant Science 17.2k
Countries citing papers authored by Wolfgang Huber
This map shows the geographic impact of Wolfgang Huber's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Wolfgang Huber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wolfgang Huber more than expected).
Fields of papers citing papers by Wolfgang Huber
This network shows the impact of papers produced by Wolfgang Huber. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Wolfgang Huber. The network helps show where Wolfgang Huber may publish in the future.
Co-authors
The 25 scholars most cited alongside Wolfgang Huber, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 281 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 Hit paper breakdown → | 2014 | 58628 |
| 2 | HTSeq—a Python framework to work with high-throughput sequencing data Hit paper breakdown → | 2014 | 14462 |
| 3 | Differential expression analysis for sequence count data Hit paper breakdown → | 2010 | 12103 |
| 4 | Software for Computing and Annotating Genomic Ranges Hit paper breakdown → | 2013 | 2620 |
| 5 | Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt Hit paper breakdown → | 2009 | 2465 |
| 6 | Variance stabilization applied to microarray data calibration and to the quantification of differential expression Hit paper breakdown → | 2002 | 1874 |
| 7 | BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis Hit paper breakdown → | 2005 | 1435 |
| 8 | Detecting differential usage of exons from RNA-seq data Hit paper breakdown → | 2012 | 1068 |
| 9 | Count-based differential expression analysis of RNA sequencing data using R and Bioconductor Hit paper breakdown → | 2013 | 861 |
| 10 | Two independent modes of chromatin organization revealed by cohesin removal Hit paper breakdown → | 2017 | 819 |
| 11 | Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets Hit paper breakdown → | 2018 | 757 |
| 12 | Bidirectional promoters generate pervasive transcription in yeast Hit paper breakdown → | 2009 | 757 |
| 13 | arrayQualityMetrics—a bioconductor package for quality assessment of microarray data Hit paper breakdown → | 2008 | 703 |
| 14 | Human haematopoietic stem cell lineage commitment is a continuous process Hit paper breakdown → | 2017 | 565 |
| 15 | A high-resolution map of transcription in the yeast genome Hit paper breakdown → | 2006 | 545 |
| 16 | EBImage—an R package for image processing with applications to cellular phenotypes Hit paper breakdown → | 2010 | 520 |
| 17 | Independent filtering increases detection power for high-throughput experiments Hit paper breakdown → | 2010 | 504 |
| 18 | Love MI, Huber W, Anders S.. Moderated estimation of fold change and dispersion for RNA-Seq data with DESeq2. Genome Biol 15: 550 Hit paper breakdown → | 2014 | 493 |
| 19 | 2008 | 476 | |
| 20 | Proteome-wide identification of ubiquitin interactions using UbIA-MS Hit paper breakdown → | 2018 | 464 |
About Wolfgang Huber
Wolfgang Huber is a scholar working on Molecular Biology, Cancer Research, Political Science and International Relations, Genetics and Genetics, having authored 281 papers that have together received 114.6k indexed citations. Recurring topics across this work include Gene expression and cancer classification (47 papers), RNA Research and Splicing (31 papers), Genomics and Chromatin Dynamics (27 papers), Bioinformatics and Genomic Networks (22 papers), Single-cell and spatial transcriptomics (17 papers), Molecular Biology Techniques and Applications (15 papers), RNA modifications and cancer (13 papers) and Chronic Lymphocytic Leukemia Research (13 papers). The work is most often cited by research in Molecular Biology (62.6k citations), Cancer Research (12.4k citations), Aging (1.4k citations), Immunology (11.6k citations) and Plant Science (17.2k citations). Wolfgang Huber has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Simon Anders, Michael I. Love, Paul Theodor Pyl, Robert Gentleman, Steffen Durinck, Ewan Birney, Paul T. Spellman, Annemarie Poustka, Alejandro Reyes and Anja von Heydebreck. Their work appears in journals such as Bioinformatics, Genome biology, Blood, Nature Methods and Molecular Systems Biology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.