Peter F. Stadler

87.4k total citations · 14 hit papers
668 papers, 38.4k citations indexed

About

Peter F. Stadler is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Peter F. Stadler has authored 668 papers receiving a total of 38.4k indexed citations (citations by other indexed papers that have themselves been cited), including 510 papers in Molecular Biology, 125 papers in Genetics and 85 papers in Cancer Research. Recurrent topics in Peter F. Stadler's work include RNA and protein synthesis mechanisms (250 papers), Genomics and Phylogenetic Studies (193 papers) and RNA modifications and cancer (148 papers). Peter F. Stadler is often cited by papers focused on RNA and protein synthesis mechanisms (250 papers), Genomics and Phylogenetic Studies (193 papers) and RNA modifications and cancer (148 papers). Peter F. Stadler collaborates with scholars based in Germany, Austria and United States. Peter F. Stadler's co-authors include Ivo L. Hofacker, Stephan Wolf, Christoph Flamm, Hakim Tafer, Walter Fontana, Frank Jühling, Peter Schuster, Matthias Bernt, Joern Pütz and Ronny Lorenz and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Peter F. Stadler

645 papers receiving 37.6k citations

Hit Papers

MITOS: Improved de novo metazoan mito... 1994 2026 2004 2015 2012 2011 1994 2010 2011 1000 2.0k 3.0k
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. MITOS: Improved de novo metazoan mitochondrial genome annotation
    2012 3.5k citations Peter F. Stadler et al. profile →
  2. ViennaRNA Package 2.0
    2011 3.4k citations Ronny Lorenz, Stephan Wolf et al. profile →
  3. Fast folding and comparison of RNA secondary structures
    1994 1.7k citations Ivo L. Hofacker, Peter F. Stadler et al. profile →
  4. The primary transcriptome of the major human pathogen Helicobacter pylori
    2010 912 citations Steve Hoffmann, Sven Findeiß et al. profile →
  5. Proteinortho: Detection of (Co-)orthologs in large-scale analysis
    2011 859 citations Sven Findeiß, Peter F. Stadler et al. profile →
  6. Prognostic value of tumor oxygenation in 397 head and neck tumors after primary radiation therapy. An international multi-center study
    2005 739 citations Peter F. Stadler et al. profile →
  7. tRNAdb 2009: compilation of tRNA sequences and tRNA genes
    2008 672 citations Mario Mörl, Peter F. Stadler et al. Nucleic Acids Research profile →
  8. From sequences to shapes and back: a case study in RNA secondary structures
    1994 578 citations Peter F. Stadler, Ivo L. Hofacker et al. profile →
  9. Interleukin-6–dependent survival of multiple myeloma cells involves the Stat3-mediated induction of microRNA-21 through a highly conserved enhancer
    2007 524 citations Dennis Löffler, Katja Brocke-Heidrich et al. Blood profile →
  10. Fast and reliable prediction of noncoding RNAs
    2005 505 citations Ivo L. Hofacker, Peter F. Stadler et al. profile →
  11. The genome of the recently domesticated crop plant sugar beet (Beta vulgaris)
    2013 478 citations Peter F. Stadler et al. profile →
  12. Improved annotation of protein-coding genes boundaries in metazoan mitochondrial genomes
    2019 423 citations Stephan Wolf, Franziska Reinhardt et al. Nucleic Acids Research profile →
  13. Dual RNA-seq unveils noncoding RNA functions in host–pathogen interactions
    2016 367 citations Fabian Amman, Peter F. Stadler et al. profile →
  14. Sound–meaning association biases evidenced across thousands of languages
    2016 272 citations Peter F. Stadler et al. profile →

Peers

Peter F. Stadler
Robert Gentleman United States
Nils Homer United States
Ewan Birney United Kingdom
Mark A. DePristo United States
Gavin Sherlock United States
Eric Banks United States
J. Michael Cherry United States
Lior Pachter United States
Steven J.M. Jones Canada
Mark Gerstein United States
Robert Gentleman United States
Peter F. Stadler
Citations per year, relative to Peter F. Stadler Peter F. Stadler (= 1×) peers Robert Gentleman

Countries citing papers authored by Peter F. Stadler

Since Specialization
Citations

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

Fields of papers citing papers by Peter F. Stadler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter F. Stadler. 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 Peter F. Stadler. The network helps show where Peter F. Stadler may publish in the future.

Co-authorship network of co-authors of Peter F. Stadler

This figure shows the co-authorship network connecting the top 25 collaborators of Peter F. Stadler. A scholar is included among the top collaborators of Peter F. Stadler 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 Peter F. Stadler. Peter F. Stadler 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.
Flamm, Christoph, Daniel Merkle, & Peter F. Stadler. (2025). Computation in chemical graph rewriting networks. Journal of Physics Complexity. 6(1). 15014–15014.
2.
Lorenz, Ronny, et al.. (2024). Phylogenetic and Chemical Probing Information as Soft Constraints in RNA Secondary Structure Prediction. Journal of Computational Biology. 31(6). 549–563. 1 indexed citations
3.
4.
Rocha, Ulisses Nunes da, René Kallies, J. Saraiva, et al.. (2023). MuDoGeR: Multi‐Domain Genome recovery from metagenomes made easy. Molecular Ecology Resources. 24(2). e13904–e13904. 14 indexed citations
5.
Gornik, Sebastian G., Víctor Flores, Franziska Reinhardt, et al.. (2022). Mitochondrial Genomes in Perkinsus Decode Conserved Frameshifts in All Genes. Molecular Biology and Evolution. 39(10). 6 indexed citations
6.
Otto, Christian, et al.. (2021). Comprehensive benchmarking of software for mapping whole genome bisulfite data: from read alignment to DNA methylation analysis. Briefings in Bioinformatics. 22(5). 18 indexed citations
7.
Kehr, Stephanie, Melanie Penke, Jana Breitfeld, et al.. (2021). PTEN regulates adipose progenitor cell growth, differentiation, and replicative aging. Journal of Biological Chemistry. 297(2). 100968–100968. 15 indexed citations
8.
Otto, Christian, Mario Fasold, Noé Fernández‐Pozo, et al.. (2021). EpiDiverse Toolkit: a pipeline suite for the analysis of bisulfite sequencing data in ecological plant epigenetics. NAR Genomics and Bioinformatics. 3(4). lqab106–lqab106. 24 indexed citations
9.
Arnold, Katharina, et al.. (2020). Beyond Plug and Pray: Context Sensitivity and in silico Design of Artificial Neomycin Riboswitches. RNA Biology. 18(4). 457–467. 7 indexed citations
10.
Maier, Lisa‐Katharina, Fabian Amman, Stephan Wolf, et al.. (2020). Identification of RNA 3´ ends and termination sites in Haloferax volcanii. RNA Biology. 17(5). 663–676. 10 indexed citations
11.
Saraiva, J., et al.. (2019). TerrestrialMetagenomeDB: a public repository of curated and standardized metadata for terrestrial metagenomes. Nucleic Acids Research. 48(D1). D626–D632. 35 indexed citations
12.
Fallmann, Jörg, Pavankumar Videm, Andrea Bagnacani, et al.. (2019). The RNA workbench 2.0: next generation RNA data analysis. Nucleic Acids Research. 47(W1). W511–W515. 12 indexed citations
13.
Stadler, Bärbel M. R., et al.. (2019). Best match graphs. White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 7 indexed citations
14.
Hoffmann, Anne, Jörg Fallmann, Elisa Vilardo, et al.. (2017). Accurate mapping of tRNA reads. Bioinformatics. 34(7). 1116–1124. 35 indexed citations
15.
Andersen, Jakob L., Christoph Flamm, Daniel Merkle, & Peter F. Stadler. (2017). Chemical Transformation Motifs—Modelling Pathways as Integer Hyperflows. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 16(2). 510–523. 30 indexed citations
16.
Lorenz, Ronny, et al.. (2015). SHAPE directed RNA folding. Bioinformatics. 32(1). 145–147. 72 indexed citations
17.
Hellmuth, Marc, Josef Leydold, & Peter F. Stadler. (2013). Convex cycle bases. Ars Mathematica Contemporanea. 7(1). 123–140. 6 indexed citations
18.
Langenberger, David, Mehmet Volkan Çakır, Steve Hoffmann, & Peter F. Stadler. (2012). Dicer‐Processed Small RNAs: Rules and Exceptions. Journal of Experimental Zoology Part B Molecular and Developmental Evolution. 320(1). 35–46. 53 indexed citations
19.
Löffler, Dennis, Katja Brocke-Heidrich, Gabriele Pfeifer, et al.. (2007). Interleukin-6–dependent survival of multiple myeloma cells involves the Stat3-mediated induction of microRNA-21 through a highly conserved enhancer. Blood. 110(4). 1330–1333. 524 indexed citations breakdown →
20.
Faulstich, Lukas C., et al.. (2003). litsift: Automated Text Categorization in Bibliographic Search. Qucosa (Saxon State and University Library Dresden). 2 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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