Maurice Scheer

4.3k total citations · 1 hit paper
15 papers, 3.3k citations indexed

About

Maurice Scheer is a scholar working on Molecular Biology, Genetics and Ecology. According to data from OpenAlex, Maurice Scheer has authored 15 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 3 papers in Genetics and 2 papers in Ecology. Recurrent topics in Maurice Scheer's work include Bioinformatics and Genomic Networks (4 papers), Genomics and Phylogenetic Studies (4 papers) and Microbial Metabolic Engineering and Bioproduction (4 papers). Maurice Scheer is often cited by papers focused on Bioinformatics and Genomic Networks (4 papers), Genomics and Phylogenetic Studies (4 papers) and Microbial Metabolic Engineering and Bioproduction (4 papers). Maurice Scheer collaborates with scholars based in Germany, Switzerland and Netherlands. Maurice Scheer's co-authors include Andreas Grote, Dieter Jahn, Richard Münch, Karsten Hiller, Bernd Nörtemann, D. C. Hempel, Dietmar Schomburg, A. Chang, Max Schobert and Michael Rother and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and PLoS ONE.

In The Last Decade

Maurice Scheer

15 papers receiving 3.2k citations

Hit Papers

JCat: a novel tool to adapt codon usage of a target gene ... 2005 2026 2012 2019 2005 250 500 750 1000
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. JCat: a novel tool to adapt codon usage of a target gene to its potential expression host
    2005 1.1k citations Andreas Grote, Karsten Hiller et al. Nucleic Acids Research profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Maurice Scheer Germany 14 2.6k 428 427 312 300 15 3.3k
Andreas Grote Germany 13 2.5k 1.0× 344 0.8× 386 0.9× 316 1.0× 297 1.0× 16 3.1k
Gunnar F. Kaufmann United States 30 2.2k 0.8× 224 0.5× 406 1.0× 268 0.9× 390 1.3× 69 3.2k
Germán L. Rosano Argentina 12 1.9k 0.7× 272 0.6× 448 1.0× 287 0.9× 137 0.5× 24 2.4k
Michel Gilbert Canada 47 3.3k 1.3× 694 1.6× 405 0.9× 443 1.4× 1000 3.3× 138 6.1k
Mogens Kilstrup Denmark 26 1.8k 0.7× 395 0.9× 873 2.0× 147 0.5× 199 0.7× 58 2.7k
Annabelle Varrot France 36 2.7k 1.0× 414 1.0× 206 0.5× 304 1.0× 189 0.6× 109 3.8k
Hyun Ah Kang South Korea 33 2.9k 1.1× 176 0.4× 178 0.4× 166 0.5× 248 0.8× 162 3.7k
Raymond Lo Canada 14 2.9k 1.1× 779 1.8× 667 1.6× 96 0.3× 440 1.5× 17 4.6k
Harshal A. Chokhawala United States 24 2.5k 1.0× 356 0.8× 177 0.4× 393 1.3× 74 0.2× 28 3.2k
Guoqing Xia Germany 27 1.5k 0.6× 656 1.5× 361 0.8× 125 0.4× 817 2.7× 44 2.4k

Countries citing papers authored by Maurice Scheer

Since Specialization
Citations

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

Fields of papers citing papers by Maurice Scheer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maurice Scheer

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

All Works

15 of 15 papers shown
1.
Scheer, Maurice, et al.. (2016). Biocompatibility of photopolymers for additive manufacturing. Current Directions in Biomedical Engineering. 2(1). 113–116. 25 indexed citations
2.
Tielen, Petra, Nathalie Y. Rosin, Katrin Dohnt, et al.. (2013). Regulatory and Metabolic Networks for the Adaptation of Pseudomonas aeruginosa Biofilms to Urinary Tract-Like Conditions. PLoS ONE. 8(8). e71845–e71845. 37 indexed citations
3.
Lavigne, Rob, Jeroen Wagemans, William Cenens, et al.. (2013). A Multifaceted Study of Pseudomonas aeruginosa Shutdown by Virulent Podovirus LUZ19. mBio. 4(2). e00061–13. 76 indexed citations
4.
Schomburg, Ida, Antje Chang, Sandra Placzek, et al.. (2012). BRENDA in 2013: integrated reactions, kinetic data, enzyme function data, improved disease classification: new options and contents in BRENDA. Nucleic Acids Research. 41(D1). D764–D772. 309 indexed citations
5.
Barkovits, Katalin, et al.. (2011). Function of the bacteriophytochrome BphP in the RpoS/Las quorum-sensing network of Pseudomonas aeruginosa. Microbiology. 157(6). 1651–1664. 22 indexed citations
6.
Trunk, Katharina, Beatrice Benkert, Richard Münch, et al.. (2010). Anaerobic adaptation in Pseudomonas aeruginosa : definition of the Anr and Dnr regulons. Environmental Microbiology. 12(6). 1719–1733. 136 indexed citations
7.
Scheer, Maurice, Andreas Grote, A. Chang, et al.. (2010). BRENDA, the enzyme information system in 2011. Nucleic Acids Research. 39(Database). D670–D676. 326 indexed citations
8.
Chang, A., et al.. (2010). The BRENDA Tissue Ontology (BTO): the first all-integrating ontology of all organisms for enzyme sources. Nucleic Acids Research. 39(Database). D507–D513. 131 indexed citations
9.
Chang, A., Maurice Scheer, Andreas Grote, & Dietmar Schomburg. (2008). BRENDA, AMENDA and FRENDA the enzyme information system: new content and tools in 2009. Nucleic Acids Research. 37(Database). D588–D592. 294 indexed citations
10.
Choi, Claudia, Richard Münch, Stefan Leupold, et al.. (2007). SYSTOMONAS -- an integrated database for systems biology analysis of Pseudomonas. Nucleic Acids Research. 35(Database). D533–D537. 41 indexed citations
11.
Scheer, Maurice, Frank Klawonn, Richard Münch, et al.. (2006). JProGO: a novel tool for the functional interpretation of prokaryotic microarray data using Gene Ontology information. Nucleic Acids Research. 34(Web Server). W510–W515. 26 indexed citations
12.
Grote, Andreas, Karsten Hiller, Maurice Scheer, et al.. (2005). JCat: a novel tool to adapt codon usage of a target gene to its potential expression host. Nucleic Acids Research. 33(Web Server). W526–W531. 1143 indexed citations breakdown →
13.
Münch, Richard, Karsten Hiller, Andreas Grote, et al.. (2005). Virtual Footprint and PRODORIC: an integrative framework for regulon prediction in prokaryotes. Bioinformatics. 21(22). 4187–4189. 305 indexed citations
14.
Hiller, Karsten, Andreas Grote, Maurice Scheer, Richard Münch, & Dieter Jahn. (2004). PrediSi: prediction of signal peptides and their cleavage positions. Nucleic Acids Research. 32(Web Server). W375–W379. 377 indexed citations
15.
Scheer, Maurice, Silvère M. van der Maarel, Angela Schulz, et al.. (2000). DXS6673E Encodes a Predominantly Nuclear Protein, and Its Mouse Ortholog DXHXS6673E Is Alternatively Spliced in a Developmental- and Tissue-Specific Manner. Genomics. 63(1). 123–132. 7 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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