Andreas Martin Lisewski

2.2k total citations
22 papers, 722 citations indexed

About

Andreas Martin Lisewski is a scholar working on Molecular Biology, Computational Theory and Mathematics and Infectious Diseases. According to data from OpenAlex, Andreas Martin Lisewski has authored 22 papers receiving a total of 722 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 5 papers in Computational Theory and Mathematics and 4 papers in Infectious Diseases. Recurrent topics in Andreas Martin Lisewski's work include Protein Structure and Dynamics (7 papers), Bioinformatics and Genomic Networks (7 papers) and Machine Learning in Bioinformatics (5 papers). Andreas Martin Lisewski is often cited by papers focused on Protein Structure and Dynamics (7 papers), Bioinformatics and Genomic Networks (7 papers) and Machine Learning in Bioinformatics (5 papers). Andreas Martin Lisewski collaborates with scholars based in United States, Germany and Sweden. Andreas Martin Lisewski's co-authors include Olivier Lichtarge, Serkan Erdin, Hyunjung Shin, S. E. Woosley, W. Hillebrandt, David M. Kristensen, R. Matthew Ward, Marek Kimmel, Lydia E. Kavraki and Janet L. Gibson and has published in prestigious journals such as Science, Cell and Nucleic Acids Research.

In The Last Decade

Andreas Martin Lisewski

22 papers receiving 703 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andreas Martin Lisewski United States 14 461 126 95 73 61 22 722
Alain Schenkel Switzerland 6 778 1.7× 157 1.2× 67 0.7× 206 2.8× 38 0.6× 7 1.2k
Christian V. Forst United States 21 987 2.1× 208 1.7× 63 0.7× 32 0.4× 115 1.9× 51 1.6k
Alpan Raval United States 20 1.0k 2.2× 307 2.4× 113 1.2× 143 2.0× 16 0.3× 39 1.6k
Rachel Kolodny Israel 19 1.3k 2.9× 66 0.5× 108 1.1× 580 7.9× 73 1.2× 44 1.5k
John Beaver United States 11 597 1.3× 40 0.3× 119 1.3× 31 0.4× 30 0.5× 15 800
Sanne Abeln Netherlands 19 738 1.6× 56 0.4× 56 0.6× 171 2.3× 16 0.3× 61 1.1k
Shiwei Sun China 18 837 1.8× 39 0.3× 133 1.4× 46 0.6× 11 0.2× 82 1.1k
Indira Ghosh India 14 343 0.7× 40 0.3× 92 1.0× 61 0.8× 70 1.1× 43 574
Conrad Steenberg United States 11 1.1k 2.5× 104 0.8× 28 0.3× 46 0.6× 13 0.2× 31 1.5k
E. R. Graf United States 7 560 1.2× 58 0.5× 94 1.0× 123 1.7× 15 0.2× 18 856

Countries citing papers authored by Andreas Martin Lisewski

Since Specialization
Citations

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

Fields of papers citing papers by Andreas Martin Lisewski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andreas Martin Lisewski

This figure shows the co-authorship network connecting the top 25 collaborators of Andreas Martin Lisewski. A scholar is included among the top collaborators of Andreas Martin Lisewski 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 Andreas Martin Lisewski. Andreas Martin Lisewski 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.
2.
Lisewski, Andreas Martin. (2021). Interim estimates in null models of COVID-19 vaccine effectiveness. International Journal of Infectious Diseases. 106. 169–170. 2 indexed citations
3.
Lisewski, Andreas Martin. (2020). Association between Influenza Vaccination Rates and SARS-CoV-2 Outbreak Infection Rates in OECD Countries. SSRN Electronic Journal. 8 indexed citations
4.
Lisewski, Andreas Martin, et al.. (2017). Potential role of Plasmodium falciparum exported protein 1 in the chloroquine mode of action. International Journal for Parasitology Drugs and Drug Resistance. 8(1). 31–35. 5 indexed citations
5.
Lisewski, Andreas Martin, Caroline L. Ng, Anbu Karani Adikesavan, et al.. (2014). Supergenomic Network Compression and the Discovery of EXP1 as a Glutathione Transferase Inhibited by Artesunate. Cell. 158(4). 916–928. 100 indexed citations
6.
Spangler, Scott, Angela D. Wilkins, Meena Nagarajan, et al.. (2014). Automated hypothesis generation based on mining scientific literature. 1877–1886. 77 indexed citations
7.
Erdin, Serkan, Eric Venner, Andreas Martin Lisewski, & Olivier Lichtarge. (2013). Function prediction from networks of local evolutionary similarity in protein structure. BMC Bioinformatics. 14(S3). S6–S6. 10 indexed citations
8.
Mamun, Abu Amar M. Al, Mary-Jane Lombardo, Chandan Shee, et al.. (2012). Identity and Function of a Large Gene Network Underlying Mutagenic Repair of DNA Breaks. Science. 338(6112). 1344–1348. 172 indexed citations
9.
Erdin, Serkan, Andreas Martin Lisewski, & Olivier Lichtarge. (2011). Protein function prediction: towards integration of similarity metrics. Current Opinion in Structural Biology. 21(2). 180–188. 32 indexed citations
10.
11.
Shin, Hyunjung, N. Jeremy Hill, Andreas Martin Lisewski, & Joon‐Sang Park. (2010). Graph sharpening. Expert Systems with Applications. 37(12). 7870–7879. 17 indexed citations
12.
Lisewski, Andreas Martin. (2008). Random Amino Acid Mutations and Protein Misfolding Lead to Shannon Limit in Sequence-Structure Communication. PLoS ONE. 3(9). e3110–e3110. 6 indexed citations
13.
Ward, R. Matthew, Serkan Erdin, T.A. Tran, et al.. (2008). De-Orphaning the Structural Proteome through Reciprocal Comparison of Evolutionarily Important Structural Features. PLoS ONE. 3(5). e2136–e2136. 20 indexed citations
14.
Kristensen, David M., R. Matthew Ward, Andreas Martin Lisewski, et al.. (2008). Prediction of enzyme function based on 3D templates of evolutionarily important amino acids. BMC Bioinformatics. 9(1). 17–17. 59 indexed citations
15.
Shin, Hyunjung, Andreas Martin Lisewski, & Olivier Lichtarge. (2007). Graph sharpening plus graph integration: a synergy that improves protein functional classification. Bioinformatics. 23(23). 3217–3224. 47 indexed citations
16.
Chen, Brian Y., Viacheslav Y. Fofanov, Drew Bryant, et al.. (2007). The MASH Pipeline for Protein Function Prediction and an Algorithm for the Geometric Refinement of 3D Motifs. Journal of Computational Biology. 14(6). 791–816. 31 indexed citations
17.
Kristensen, David M., Brian Y. Chen, Viacheslav Y. Fofanov, et al.. (2006). Recurrent use of evolutionary importance for functional annotation of proteins based on local structural similarity. Protein Science. 15(6). 1530–1536. 24 indexed citations
18.
Lisewski, Andreas Martin & Olivier Lichtarge. (2006). Rapid detection of similarity in protein structure and function through contact metric distances. Nucleic Acids Research. 34(22). e152–e152. 24 indexed citations
19.
Lisewski, Andreas Martin. (2006). The concept of strong and weak virtual reality. Minds and Machines. 16(2). 201–219. 3 indexed citations
20.
Lisewski, Andreas Martin, W. Hillebrandt, S. E. Woosley, J. C. Niemeyer, & Alan R. Kerstein. (2000). Distributed Burning in Type Ia Supernovae: A Statistical Approach. The Astrophysical Journal. 537(1). 405–413. 24 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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