Stephan Waack

9.5k total citations · 4 hit papers
47 papers, 5.6k citations indexed

About

Stephan Waack is a scholar working on Molecular Biology, Computational Theory and Mathematics and Computer Networks and Communications. According to data from OpenAlex, Stephan Waack has authored 47 papers receiving a total of 5.6k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 18 papers in Computational Theory and Mathematics and 6 papers in Computer Networks and Communications. Recurrent topics in Stephan Waack's work include Machine Learning in Bioinformatics (14 papers), RNA and protein synthesis mechanisms (14 papers) and Genomics and Phylogenetic Studies (13 papers). Stephan Waack is often cited by papers focused on Machine Learning in Bioinformatics (14 papers), RNA and protein synthesis mechanisms (14 papers) and Genomics and Phylogenetic Studies (13 papers). Stephan Waack collaborates with scholars based in Germany, Netherlands and Switzerland. Stephan Waack's co-authors include Mario Stanke, Burkhard Morgenstern, Irfan Gunduz, Ashley Hayes, O. Keller, Ralph Steinkamp, Oliver Keller, Martin Kollmar, Carsten Damm and W. Florian Fricke and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Bioinformatics.

In The Last Decade

Stephan Waack

42 papers receiving 5.6k citations

Hit Papers

AUGUSTUS: ab initio prediction of alternative transcripts 2003 2026 2010 2018 2006 2003 2004 2006 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephan Waack Germany 17 3.3k 2.2k 1.0k 703 650 47 5.6k
John Maslen United Kingdom 3 3.6k 1.1× 2.1k 0.9× 835 0.8× 1.2k 1.7× 443 0.7× 3 6.2k
A. F. Quinn United Kingdom 4 3.3k 1.0× 2.0k 0.9× 811 0.8× 1.2k 1.7× 442 0.7× 5 5.9k
David Binns United Kingdom 8 4.6k 1.4× 2.2k 1.0× 981 0.9× 1.3k 1.8× 497 0.8× 9 7.5k
Philip Jones United Kingdom 23 4.4k 1.3× 2.1k 0.9× 920 0.9× 1.2k 1.7× 493 0.8× 54 7.8k
Sarah Hunter United Kingdom 6 3.3k 1.0× 2.1k 1.0× 829 0.8× 1.2k 1.7× 449 0.7× 10 5.9k
Siew-Yit Yong United Kingdom 3 3.3k 1.0× 2.1k 0.9× 818 0.8× 1.2k 1.7× 446 0.7× 3 5.9k
Stefan Götz Germany 21 3.2k 1.0× 2.4k 1.1× 960 0.9× 786 1.1× 348 0.5× 54 7.2k
Sebastien Pesseat United Kingdom 4 3.4k 1.0× 2.1k 0.9× 819 0.8× 1.3k 1.8× 442 0.7× 4 6.0k
Konstantin Berlin United States 11 3.5k 1.0× 2.0k 0.9× 694 0.7× 1.0k 1.4× 402 0.6× 19 6.0k

Countries citing papers authored by Stephan Waack

Since Specialization
Citations

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

Fields of papers citing papers by Stephan Waack

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stephan Waack

This figure shows the co-authorship network connecting the top 25 collaborators of Stephan Waack. A scholar is included among the top collaborators of Stephan Waack 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 Stephan Waack. Stephan Waack 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.
Habeck, Michael, et al.. (2021). A graph-based algorithm for detecting rigid domains in protein structures. BMC Bioinformatics. 22(1). 66–66. 1 indexed citations
2.
Hatje, Klas, et al.. (2021). Critical assessment of coiled-coil predictions based on protein structure data. Scientific Reports. 11(1). 12439–12439. 15 indexed citations
3.
Hua, Xu, et al.. (2015). PC-TraFF: identification of potentially collaborating transcription factors using pointwise mutual information. BMC Bioinformatics. 16(1). 400–400. 21 indexed citations
5.
Gültaş, Mehmet, Martin Haubrock, Nesrin Tüysüz, & Stephan Waack. (2012). Coupled mutation finder: A new entropy-based method quantifying phylogenetic noise for the detection of compensatory mutations. BMC Bioinformatics. 13(1). 225–225. 8 indexed citations
6.
Hatje, Klas, et al.. (2011). Cross-species protein sequence and gene structure prediction with fine-tuned Webscipio 2.0 and Scipio. BMC Research Notes. 4(1). 265–265. 38 indexed citations
7.
Keller, Oliver, Florian Odronitz, Mario Stanke, Martin Kollmar, & Stephan Waack. (2008). Scipio: Using protein sequences to determine the precise exon/intron structures of genes and their orthologs in closely related species. BMC Bioinformatics. 9(1). 278–278. 99 indexed citations
8.
Odronitz, Florian, et al.. (2008). WebScipio: An online tool for the determination of gene structures using protein sequences. BMC Genomics. 9(1). 422–422. 26 indexed citations
9.
Stanke, Mario, et al.. (2006). Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources. BMC Bioinformatics. 7(1). 62–62. 837 indexed citations breakdown →
10.
Stanke, Mario, O. Keller, Irfan Gunduz, et al.. (2006). AUGUSTUS: ab initio prediction of alternative transcripts. Nucleic Acids Research. 34(Web Server). W435–W439. 1642 indexed citations breakdown →
11.
Waack, Stephan, Oliver Keller, Carsten Damm, et al.. (2006). Score-based prediction of genomic islands in prokaryotic genomes using hidden Markov models. BMC Bioinformatics. 7(1). 142–142. 285 indexed citations
12.
Damm, Carsten, Matthias Krause, Christoph Meinel, & Stephan Waack. (2004). On relations between counting communication complexity classes. Journal of Computer and System Sciences. 69(2). 259–280. 10 indexed citations
13.
Stanke, Mario, Ralph Steinkamp, Stephan Waack, & Burkhard Morgenstern. (2004). AUGUSTUS: a web server for gene finding in eukaryotes. Nucleic Acids Research. 32(Web Server). W309–W312. 903 indexed citations breakdown →
14.
Waack, Stephan. (2001). On the Descriptive and Algorithmic Power of Parity Ordered Binary Decision Diagrams. Information and Computation. 166(1). 61–70. 1 indexed citations
15.
Meinel, Christoph & Stephan Waack. (1994). The Möbius Function, Variations Ranks, and Theta(n)-Bounds on the Modular Communication Complexity of the Undirected Graph Connectivity Problem. Electronic colloquium on computational complexity. 1. 1 indexed citations
16.
Krause, Matthias, Christoph Meinel, & Stephan Waack. (1991). Separating the eraser Turing machine classes Le, NLe, co-NLe and Pe. Theoretical Computer Science. 86(2). 267–275. 19 indexed citations
17.
Krause, Matthias & Stephan Waack. (1991). On oblivious branching programs of linear length. Information and Computation. 94(2). 232–249. 13 indexed citations
18.
Waack, Stephan. (1990). The Parallel Complexity of Some Constructions in Combinatorial Group Theory.. Journal of automata, languages and combinatorics. 26. 265–281. 3 indexed citations
19.
Meinel, Christoph, et al.. (1988). Algebraic and topological properties of finite partially ordered sets. 10 indexed citations
20.
Waack, Stephan, et al.. (1982). On the Halting Problem for Automata in Cones.. Journal of automata, languages and combinatorics. 18. 489–499. 1 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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