Simon Anders

157.0k total citations · 8 hit papers
59 papers, 87.9k citations indexed

About

Simon Anders is a scholar working on Molecular Biology, Immunology and Cancer Research. According to data from OpenAlex, Simon Anders has authored 59 papers receiving a total of 87.9k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Molecular Biology, 9 papers in Immunology and 9 papers in Cancer Research. Recurrent topics in Simon Anders's work include Gene expression and cancer classification (11 papers), RNA Research and Splicing (11 papers) and RNA modifications and cancer (10 papers). Simon Anders is often cited by papers focused on Gene expression and cancer classification (11 papers), RNA Research and Splicing (11 papers) and RNA modifications and cancer (10 papers). Simon Anders collaborates with scholars based in Germany, United States and United Kingdom. Simon Anders's co-authors include Wolfgang Huber, Michael I. Love, Paul Theodor Pyl, Alejandro Reyes, Gordon K. Smyth, Mark D. Robinson, Davis J. McCarthy, Michał Okoniewski, Yunshun Chen and Vladimı́r Beneš and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Simon Anders

58 papers receiving 87.4k citations

Hit Papers

Moderated estimation of fold change and dispersion for RN... 2010 2026 2015 2020 2014 2014 2010 2012 2013 10.0k 20.0k 30.0k 40.0k 50.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
    2014 55.9k citations Wolfgang Huber, Simon Anders et al. profile →
  2. HTSeq—a Python framework to work with high-throughput sequencing data
    2014 14.1k citations Simon Anders, Paul Theodor Pyl et al. Bioinformatics profile →
  3. Differential expression analysis for sequence count data
    2010 11.8k citations Simon Anders, Wolfgang Huber profile →
  4. Detecting differential usage of exons from RNA-seq data
    2012 1.0k citations Simon Anders, Wolfgang Huber et al. Genome Research profile →
  5. Count-based differential expression analysis of RNA sequencing data using R and Bioconductor
    2013 841 citations Simon Anders, Wolfgang Huber et al. profile →
  6. Accounting for technical noise in single-cell RNA-seq experiments
    2013 676 citations Simon Anders et al. Nature Methods profile →
  7. Love MI, Huber W, Anders S.. Moderated estimation of fold change and dispersion for RNA-Seq data with DESeq2. Genome Biol 15: 550
    2014 490 citations Wolfgang Huber, Simon Anders et al. profile →
  8. A colorimetric RT-LAMP assay and LAMP-sequencing for detecting SARS-CoV-2 RNA in clinical samples
    2020 482 citations Viet Loan Dao Thi, Konrad Herbst et al. Science Translational Medicine profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Simon Anders Germany 31 51.5k 15.8k 11.8k 10.7k 9.6k 59 87.9k
Michael I. Love United States 31 39.1k 0.8× 11.3k 0.7× 8.9k 0.8× 8.8k 0.8× 7.0k 0.7× 93 68.1k
Wolfgang Huber Germany 72 67.0k 1.3× 17.8k 1.1× 14.6k 1.2× 12.8k 1.2× 12.6k 1.3× 249 109.8k
Cole Trapnell United States 60 58.9k 1.1× 16.3k 1.0× 16.6k 1.4× 9.6k 0.9× 9.4k 1.0× 102 85.0k
Minoru Kanehisa Japan 75 76.3k 1.5× 14.1k 0.9× 12.2k 1.0× 8.7k 0.8× 10.1k 1.1× 266 114.1k
Jun Wang China 107 34.0k 0.7× 11.7k 0.7× 7.9k 0.7× 5.4k 0.5× 9.5k 1.0× 1.9k 66.2k
Christian von Mering Switzerland 68 45.6k 0.9× 7.0k 0.4× 7.5k 0.6× 5.6k 0.5× 6.3k 0.7× 134 69.7k
Ben Langmead United States 31 49.5k 1.0× 18.4k 1.2× 8.7k 0.7× 6.0k 0.6× 11.2k 1.2× 79 79.0k
Peer Bork Germany 151 97.1k 1.9× 18.8k 1.2× 9.5k 0.8× 10.0k 0.9× 15.3k 1.6× 524 145.9k
Gordon K. Smyth Australia 87 69.9k 1.4× 14.0k 0.9× 20.6k 1.8× 18.5k 1.7× 13.2k 1.4× 345 122.5k
Michael W. Pfaffl Germany 47 30.7k 0.6× 9.5k 0.6× 6.1k 0.5× 7.1k 0.7× 6.7k 0.7× 247 62.0k

Countries citing papers authored by Simon Anders

Since Specialization
Citations

This map shows the geographic impact of Simon Anders'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 Simon Anders with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simon Anders more than expected).

Fields of papers citing papers by Simon Anders

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Simon Anders. 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 Simon Anders. The network helps show where Simon Anders may publish in the future.

Co-authorship network of co-authors of Simon Anders

This figure shows the co-authorship network connecting the top 25 collaborators of Simon Anders. A scholar is included among the top collaborators of Simon Anders based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Simon Anders. Simon Anders is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Rademacher, Anne, Sabrina Schumacher, Petros Kolovos, et al.. (2025). Two distinct chromatin modules regulate proinflammatory gene expression. Nature Cell Biology. 28(1). 182–196.
2.
Ahlmann-Eltze, Constantin, Wolfgang Huber, & Simon Anders. (2025). Deep-learning-based gene perturbation effect prediction does not yet outperform simple linear baselines. Nature Methods. 22(8). 1657–1661. 12 indexed citations
3.
Kremer, Lukas P. M., Santiago Cerrizuela, Hadil El‐Sammak, et al.. (2024). DNA methylation controls stemness of astrocytes in health and ischaemia. Nature. 634(8033). 415–423. 11 indexed citations
4.
Li, Xue, et al.. (2023). Centrosome linker diversity and its function in centrosome clustering and mitotic spindle formation. The EMBO Journal. 42(17). e109738–e109738. 10 indexed citations
5.
Ovchinnikova, Svetlana, et al.. (2023). Sex-biased gene expression across mammalian organ development and evolution. Science. 382(6670). eadf1046–eadf1046. 39 indexed citations
6.
Witzel, Simon, Felix Frauhammer, Petra Steinacker, et al.. (2021). Neurofilament light and heterogeneity of disease progression in amyotrophic lateral sclerosis: development and validation of a prediction model to improve interventional trials. Translational Neurodegeneration. 10(1). 31–31. 20 indexed citations
7.
Herbst, Konrad, Matthias Meurer, Daniel Kirrmaier, et al.. (2021). Colorimetric RT-LAMP and LAMP-sequencing for Detecting SARS-CoV-2 RNA in Clinical Samples. BIO-PROTOCOL. 11(6). e3964–e3964. 3 indexed citations
8.
Thi, Viet Loan Dao, Konrad Herbst, Kathleen Boerner, et al.. (2020). A colorimetric RT-LAMP assay and LAMP-sequencing for detecting SARS-CoV-2 RNA in clinical samples. Science Translational Medicine. 12(556). 482 indexed citations breakdown →
9.
Wang, Zhongyi, Evgeny Leushkin, Angélica Liechti, et al.. (2020). Transcriptome and translatome co-evolution in mammals. Nature. 588(7839). 642–647. 109 indexed citations
10.
Zhu, Yafeng, Lukas M. Orre, Georgios Mermelekas, et al.. (2020). DEqMS: A Method for Accurate Variance Estimation in Differential Protein Expression Analysis. Molecular & Cellular Proteomics. 19(6). 1047–1057. 128 indexed citations
11.
Foulkes, Amy, David Watson, Daniel F. Carr, et al.. (2018). A Framework for Multi-Omic Prediction of Treatment Response to Biologic Therapy for Psoriasis. Journal of Investigative Dermatology. 139(1). 100–107. 37 indexed citations
12.
Närhi, Katja Maria, Ashwini S. Nagaraj, Elina Parri, et al.. (2018). Spatial aspects of oncogenic signalling determine the response to combination therapy in slice explants from Kras‐driven lung tumours. The Journal of Pathology. 245(1). 101–113. 19 indexed citations
13.
Klein, Felix A., Tibor Pakozdi, Simon Anders, et al.. (2015). FourCSeq: analysis of 4C sequencing data. Bioinformatics. 31(19). 3085–3091. 67 indexed citations
14.
Hauer, Christian, Tomaž Curk, Simon Anders, et al.. (2015). Improved binding site assignment by high-resolution mapping of RNA–protein interactions using iCLIP. Nature Communications. 6(1). 7921–7921. 26 indexed citations
15.
Anders, Simon, Paul Theodor Pyl, & Wolfgang Huber. (2014). HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics. 31(2). 166–169. 14076 indexed citations breakdown →
16.
Schlattl, Andreas, Simon Anders, Sebastian M. Waszak, Wolfgang Huber, & Jan O. Korbel. (2011). Relating CNVs to transcriptome data at fine resolution: Assessment of the effect of variant size, type, and overlap with functional regions. Genome Research. 21(12). 2004–2013. 88 indexed citations
17.
Anders, Simon. (2011). Analysing RNA-Seq data with the DESeq package. 15(7). 1768–81. 135 indexed citations
18.
Anders, Simon. (2009). Visualization of genomic data with the Hilbert curve. Bioinformatics. 25(10). 1231–1235. 49 indexed citations
19.
Topka, Sabine, Simon Anders, Gunnar Weisheit, et al.. (2008). Basic molecular fingerprinting of immature cerebellar cortical inhibitory interneurons and their precursors. Neuroscience. 159(1). 69–82. 16 indexed citations
20.
Anders, Simon & Hans J. Briegel. (2006). Fast simulation of stabilizer circuits using a graph-state representation. Physical Review A. 73(2). 89 indexed citations

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.

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