Martin Kircher

40.8k total citations · 13 hit papers
71 papers, 15.1k citations indexed

About

Martin Kircher is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Martin Kircher has authored 71 papers receiving a total of 15.1k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Molecular Biology, 25 papers in Genetics and 11 papers in Cancer Research. Recurrent topics in Martin Kircher's work include Genomics and Phylogenetic Studies (19 papers), Genomics and Rare Diseases (14 papers) and RNA and protein synthesis mechanisms (13 papers). Martin Kircher is often cited by papers focused on Genomics and Phylogenetic Studies (19 papers), Genomics and Rare Diseases (14 papers) and RNA and protein synthesis mechanisms (13 papers). Martin Kircher collaborates with scholars based in Germany, United States and Canada. Martin Kircher's co-authors include Jay Shendure, Daniela Witten, Gregory M. Cooper, Matthias Meyer, Brian J. O’Roak, Philipp Rentzsch, Janet Kelso, Svante Pääbo, Susanna Sawyer and Matthew W. Snyder and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Martin Kircher

68 papers receiving 15.0k citations

Hit Papers

A general framework for estimating the relative pathogeni... 2009 2026 2014 2020 2014 2018 2010 2016 2011 1000 2.0k 3.0k

Peers

Martin Kircher
Comparison fields: 5 of 186
  • Molecular Biology 9.0k
  • Genetics 6.4k
  • Cancer Research 2.1k
  • Ecology 1.1k
  • Archeology 759
Replace Lynn B. Jorde with:
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Lynn B. Jorde United States View profile →
Citations per field, relative to Martin Kircher
Martin Kircher · 1×
Citations per year, relative to Martin Kircher
Martin Kircher · 1×

Countries citing papers authored by Martin Kircher

Since Specialization
Citations

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

Fields of papers citing papers by Martin Kircher

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Kircher

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Kircher. A scholar is included among the top collaborators of Martin Kircher 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 Martin Kircher. Martin Kircher 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
# Work Indexed citations
1 4
2 1
3 0
4
CADD v1.7: using protein language models, regulatory CNNs and other nucleotide-level scores to improve genome-wide variant predictions breakdown →
112
5 35
6 1
7 16
8 113
9 70
10 1
11 8
12 19
13 131
14 10
15 254
16 26
17 179
18 25
19 314
20 114

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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