Robert Rentzsch

2.5k total citations
13 papers, 894 citations indexed

About

Robert Rentzsch is a scholar working on Molecular Biology, Organic Chemistry and Computational Theory and Mathematics. According to data from OpenAlex, Robert Rentzsch has authored 13 papers receiving a total of 894 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 1 paper in Organic Chemistry and 1 paper in Computational Theory and Mathematics. Recurrent topics in Robert Rentzsch's work include Genomics and Phylogenetic Studies (9 papers), Machine Learning in Bioinformatics (7 papers) and Bioinformatics and Genomic Networks (4 papers). Robert Rentzsch is often cited by papers focused on Genomics and Phylogenetic Studies (9 papers), Machine Learning in Bioinformatics (7 papers) and Bioinformatics and Genomic Networks (4 papers). Robert Rentzsch collaborates with scholars based in United Kingdom, Germany and Italy. Robert Rentzsch's co-authors include Christine Orengo, Bernhard Y. Renard, David Lee, Corin Yeats, Jonathan Lees, Nicholas Furnham, Janet M. Thornton, Alison Cuff, Carlus Deneke and Sarah Addou and has published in prestigious journals such as Nature, Nucleic Acids Research and Bioinformatics.

In The Last Decade

Robert Rentzsch

13 papers receiving 877 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Robert Rentzsch United Kingdom 12 768 115 115 75 59 13 894
Elisabeth Coudert Switzerland 13 756 1.0× 62 0.5× 82 0.7× 97 1.3× 67 1.1× 19 911
Shashi Bhushan Pandit India 13 569 0.7× 127 1.1× 77 0.7× 26 0.3× 50 0.8× 35 698
Nicola Bordin United Kingdom 16 642 0.8× 139 1.2× 70 0.6× 89 1.2× 79 1.3× 31 881
Carola Söhngen Germany 6 683 0.9× 65 0.6× 71 0.6× 86 1.1× 45 0.8× 7 848
Sergio Martínez Cuesta United Kingdom 20 1.3k 1.7× 85 0.7× 65 0.6× 56 0.7× 107 1.8× 28 1.5k
Parit Bansal Switzerland 4 593 0.8× 34 0.3× 90 0.8× 74 1.0× 80 1.4× 6 788
Jinrui Xu United States 6 652 0.8× 176 1.5× 86 0.7× 39 0.5× 90 1.5× 18 817
P. Sampathkumar United States 8 626 0.8× 133 1.2× 89 0.8× 42 0.6× 57 1.0× 11 921
Goran Neshich Brazil 19 536 0.7× 85 0.7× 87 0.8× 36 0.5× 108 1.8× 48 756
Jianzhao Gao China 16 750 1.0× 150 1.3× 146 1.3× 27 0.4× 29 0.5× 35 875

Countries citing papers authored by Robert Rentzsch

Since Specialization
Citations

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

Fields of papers citing papers by Robert Rentzsch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Robert Rentzsch

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

All Works

13 of 13 papers shown
1.
Rentzsch, Robert, et al.. (2019). DeePaC: predicting pathogenic potential of novel DNA with reverse-complement neural networks. Bioinformatics. 36(1). 81–89. 38 indexed citations
2.
Rentzsch, Robert, Carlus Deneke, Andreas Nitsche, & Bernhard Y. Renard. (2019). Predicting bacterial virulence factors – evaluation of machine learning and negative data strategies. Briefings in Bioinformatics. 21(5). 1596–1608. 22 indexed citations
3.
Deneke, Carlus, Robert Rentzsch, & Bernhard Y. Renard. (2017). PaPrBaG: A machine learning approach for the detection of novel pathogens from NGS data. Scientific Reports. 7(1). 39194–39194. 51 indexed citations
4.
Rentzsch, Robert & Bernhard Y. Renard. (2015). Docking small peptides remains a great challenge: an assessment using AutoDock Vina. Briefings in Bioinformatics. 16(6). 1045–1056. 122 indexed citations
5.
Rentzsch, Robert & Christine Orengo. (2013). Protein function prediction using domain families. BMC Bioinformatics. 14(S3). S5–S5. 59 indexed citations
6.
Lees, Jonathan, Romain A. Studer, Natalie L. Dawson, et al.. (2013). Gene3D: Multi-domain annotations for protein sequence and comparative genome analysis. Nucleic Acids Research. 42(D1). D240–D245. 43 indexed citations
7.
Sillitoe, Ian, Alison Cuff, Benoît H. Dessailly, et al.. (2012). New functional families (FunFams) in CATH to improve the mapping of conserved functional sites to 3D structures. Nucleic Acids Research. 41(D1). D490–D498. 171 indexed citations
8.
Lees, Jonathan, et al.. (2011). Gene3D: a domain-based resource for comparative genomics, functional annotation and protein network analysis. Nucleic Acids Research. 40(D1). D465–D471. 81 indexed citations
9.
Cuff, Alison, Ted G. Lewis, A.B. Clegg, et al.. (2010). Extending CATH: increasing coverage of the protein structure universe and linking structure with function. Nucleic Acids Research. 39(Database). D420–D426. 100 indexed citations
10.
Rentzsch, Robert & Christine Orengo. (2009). Protein function prediction – the power of multiplicity. Trends in biotechnology. 27(4). 210–219. 89 indexed citations
11.
Rentzsch, Robert, et al.. (2009). GeMMA: functional subfamily classification within superfamilies of predicted protein structural domains. Nucleic Acids Research. 38(3). 720–737. 44 indexed citations
12.
Addou, Sarah, Robert Rentzsch, David Lee, & Christine Orengo. (2008). Domain-Based and Family-Specific Sequence Identity Thresholds Increase the Levels of Reliable Protein Function Transfer. Journal of Molecular Biology. 387(2). 416–430. 73 indexed citations
13.
Rentzsch, Robert. (2006). After-school programmes. Nature. 440(7080). 122–123. 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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