Matthias Geihs

2.6k total citations
9 papers, 146 citations indexed

About

Matthias Geihs is a scholar working on Artificial Intelligence, Information Systems and Molecular Biology. According to data from OpenAlex, Matthias Geihs has authored 9 papers receiving a total of 146 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 4 papers in Information Systems and 3 papers in Molecular Biology. Recurrent topics in Matthias Geihs's work include Cryptography and Data Security (5 papers), Cloud Data Security Solutions (3 papers) and RNA modifications and cancer (2 papers). Matthias Geihs is often cited by papers focused on Cryptography and Data Security (5 papers), Cloud Data Security Solutions (3 papers) and RNA modifications and cancer (2 papers). Matthias Geihs collaborates with scholars based in Germany, United Kingdom and China. Matthias Geihs's co-authors include Nicole Soranzo, Josine L. Min, Nicholas J. Timpson, Klaudia Walter, Ian Dunham, Valentina Iotchkova, Ewan Birney, Graham R. S. Ritchie, Johannes Buchmann and Sandro Morganella and has published in prestigious journals such as Nature Genetics, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Matthias Geihs

9 papers receiving 143 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Matthias Geihs Germany	6	64	62	26	17	15	9	146
Nina K. Wenke Germany	8	54 0.8×	46 0.7×	60 2.3×	12 0.7×	11 0.7×	10	223
Zuotian Tatum Netherlands	7	65 1.0×	22 0.4×	21 0.8×	18 1.1×	16 1.1×	11	118
Joeri K. van der Velde Netherlands	4	108 1.7×	110 1.8×	17 0.7×	5 0.3×	12 0.8×	4	209
Matthew N. Bainbridge United States	2	56 0.9×	50 0.8×	8 0.3×	6 0.4×	9 0.6×	4	116
Dustin Olley United States	5	209 3.3×	41 0.7×	29 1.1×	6 0.4×	5 0.3×	5	261
Jiwen Xin United States	5	111 1.7×	32 0.5×	9 0.3×	7 0.4×	11 0.7×	9	154
Shirong Ma China	9	65 1.0×	15 0.2×	39 1.5×	8 0.5×	10 0.7×	23	226
Rebecca Jackson United States	4	209 3.3×	40 0.6×	66 2.5×	4 0.2×	18 1.2×	5	276
Yogasudha Veturi United States	10	106 1.7×	164 2.6×	12 0.5×	12 0.7×	2 0.1×	17	265
Tobias Frisch Germany	7	75 1.2×	16 0.3×	61 2.3×	22 1.3×	11 0.7×	10	197

Countries citing papers authored by Matthias Geihs

Since Specialization

Citations

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

Fields of papers citing papers by Matthias Geihs

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthias Geihs

This figure shows the co-authorship network connecting the top 25 collaborators of Matthias Geihs. A scholar is included among the top collaborators of Matthias Geihs 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 Matthias Geihs. Matthias Geihs is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Geihs, Matthias, et al.. (2020). ELSA: efficient long-term secure storage of large datasets (full version) ∗. SHILAP Revista de lepidopterología. 2020(1). 2 indexed citations

2.

Iotchkova, Valentina, Graham R. S. Ritchie, Matthias Geihs, et al.. (2019). GARFIELD classifies disease-relevant genomic features through integration of functional annotations with association signals. Nature Genetics. 51(2). 343–353. 94 indexed citations

3.

Buchmann, Johannes, et al.. (2019). Long-term integrity protection of genomic data. SHILAP Revista de lepidopterología. 2019(1). 2 indexed citations

4.

Geihs, Matthias, et al.. (2018). PQChain: Strategic Design Decisions for Distributed Ledger Technologies against Future Threats. IEEE Security & Privacy. 16(4). 57–65. 8 indexed citations

5.

Martin, Joshua S., John P. McGee, Yuchen Yang, et al.. (2017). A SNP panel and online tool for checking genotype concordance through comparing QR codes. PLoS ONE. 12(9). e0182438–e0182438. 6 indexed citations

6.

Buchmann, Johannes, et al.. (2017). Quantum cryptography: a view from classical cryptography. Quantum Science and Technology. 2(2). 20502–20502. 9 indexed citations

7.

Buchmann, Johannes, Matthias Geihs, Mikio Fujiwara, et al.. (2017). LINCOS. TUbilio (Technical University of Darmstadt). 461–468. 13 indexed citations

8.

Geihs, Matthias, et al.. (2016). A security analysis of techniques for long-term integrity protection. 2008. 449–456. 4 indexed citations

9.

Geihs, Matthias, Yan Yan, Klaudia Walter, et al.. (2015). An interactive genome browser of association results from the UK10K cohorts project. Bioinformatics. 31(24). 4029–4031. 8 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.

Explore authors with similar magnitude of impact