Astrid Maaß

742 total citations
25 papers, 579 citations indexed

About

Astrid Maaß is a scholar working on Molecular Biology, Computational Theory and Mathematics and Physiology. According to data from OpenAlex, Astrid Maaß has authored 25 papers receiving a total of 579 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 4 papers in Computational Theory and Mathematics and 4 papers in Physiology. Recurrent topics in Astrid Maaß's work include Genetics, Bioinformatics, and Biomedical Research (4 papers), Adenosine and Purinergic Signaling (4 papers) and Protein Structure and Dynamics (3 papers). Astrid Maaß is often cited by papers focused on Genetics, Bioinformatics, and Biomedical Research (4 papers), Adenosine and Purinergic Signaling (4 papers) and Protein Structure and Dynamics (3 papers). Astrid Maaß collaborates with scholars based in Germany, France and United States. Astrid Maaß's co-authors include Christa E. Müller, Joachim C. Burbiel, Karl N. Kirschner, Thereza A. Soares, Roberto D. Lins, Farag F. Sherbiny, Anke C. Schiedel, Dirk Reith, Martin Hofmann‐Apitius and Dominik Thimm and has published in prestigious journals such as Biochemistry, European Journal of Biochemistry and Biochemical Pharmacology.

In The Last Decade

Astrid Maaß

24 papers receiving 573 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Astrid Maaß Germany 13 339 168 71 67 58 25 579
Adnan Sljoka Canada 14 582 1.7× 42 0.3× 148 2.1× 32 0.5× 40 0.7× 30 777
L. Michel Espinoza‐Fonseca United States 20 833 2.5× 33 0.2× 98 1.4× 125 1.9× 119 2.1× 59 1.1k
Rie Tanaka Japan 14 360 1.1× 30 0.2× 75 1.1× 13 0.2× 14 0.2× 33 681
Ismael Rodríguez‐Espigares Spain 7 395 1.2× 20 0.1× 106 1.5× 29 0.4× 43 0.7× 10 466
D.S. Williamson United Kingdom 16 693 2.0× 56 0.3× 44 0.6× 272 4.1× 118 2.0× 26 1.2k
Rodolfo Briones Germany 14 682 2.0× 7 0.0× 173 2.4× 69 1.0× 16 0.3× 21 866
Mengyu Wu United States 14 555 1.6× 45 0.3× 100 1.4× 9 0.1× 14 0.2× 30 990
Christopher Ing Canada 15 532 1.6× 10 0.1× 260 3.7× 36 0.5× 11 0.2× 22 828
I. V. Uporov Russia 18 469 1.4× 18 0.1× 73 1.0× 18 0.3× 24 0.4× 58 754
Dennis Sprous United States 13 709 2.1× 10 0.1× 47 0.7× 111 1.7× 116 2.0× 21 1.0k

Countries citing papers authored by Astrid Maaß

Since Specialization
Citations

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

Fields of papers citing papers by Astrid Maaß

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Astrid Maaß

This figure shows the co-authorship network connecting the top 25 collaborators of Astrid Maaß. A scholar is included among the top collaborators of Astrid Maaß 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 Astrid Maaß. Astrid Maaß 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.
Maaß, Astrid, et al.. (2024). Llamol: a dynamic multi-conditional generative transformer for de novo molecular design. Journal of Cheminformatics. 16(1). 73–73. 7 indexed citations
2.
Barker, James, et al.. (2021). Rapid Prescreening of Organic Compounds for Redox Flow Batteries: A Graph Convolutional Network for Predicting Reaction Enthalpies from SMILES. Batteries & Supercaps. 4(9). 1482–1490. 7 indexed citations
3.
Maaß, Astrid, et al.. (2018). Insights into the Folding of Disulfide-Rich μ-Conotoxins. ACS Omega. 3(10). 12330–12340. 18 indexed citations
4.
Tietze, Alesia A., Frank Bordusa, Ralf Giernoth, et al.. (2013). On the Nature of Interactions between Ionic Liquids and Small Amino‐Acid‐Based Biomolecules. ChemPhysChem. 14(18). 4044–4064. 59 indexed citations
5.
Thimm, Dominik, Anke C. Schiedel, Farag F. Sherbiny, et al.. (2013). Ligand-Specific Binding and Activation of the Human Adenosine A2BReceptor. Biochemistry. 52(4). 726–740. 35 indexed citations
6.
Kirschner, Karl N., Roberto D. Lins, Astrid Maaß, & Thereza A. Soares. (2012). A Glycam-Based Force Field for Simulations of Lipopolysaccharide Membranes: Parametrization and Validation. Journal of Chemical Theory and Computation. 8(11). 4719–4731. 87 indexed citations
7.
Schiedel, Anke C., Sonja Hinz, Dominik Thimm, et al.. (2011). The four cysteine residues in the second extracellular loop of the human adenosine A2B receptor: Role in ligand binding and receptor function. Biochemical Pharmacology. 82(4). 389–399. 33 indexed citations
8.
Maaß, Astrid, et al.. (2010). Folding and unfolding characteristics of short beta strand peptides under different environmental conditions and starting configurations. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics. 1804(10). 2003–2015. 7 indexed citations
9.
Vrabec, Jadran, et al.. (2010). Assessment of numerical optimization algorithms for the development of molecular models. Computer Physics Communications. 181(5). 887–905. 21 indexed citations
10.
Köddermann, Thorsten, et al.. (2010). Molecular Dynamics Simulation: A Powerful Tool for Engineering Condensed Matter. Chemie Ingenieur Technik. 82(9). 1391–1391.
11.
Sherbiny, Farag F., Anke C. Schiedel, Astrid Maaß, & Christa E. Müller. (2009). Homology modelling of the human adenosine A2B receptor based on X-ray structures of bovine rhodopsin, the β2-adrenergic receptor and the human adenosine A2A receptor. Journal of Computer-Aided Molecular Design. 23(11). 807–828. 36 indexed citations
12.
Kasam, Vinod, Jean Salzemann, Gianluca Degliesposti, et al.. (2009). WISDOM-II: Screening against multiple targets implicated in malaria using computational grid infrastructures. Malaria Journal. 8(1). 88–88. 32 indexed citations
13.
Scholz, Joachim, Karen Toska, Alexander Luborzewski, et al.. (2008). Endogenous tetrahydroisoquinolines associated with Parkinson’s disease mimic the feedback inhibition of tyrosine hydroxylase by catecholamines. FEBS Journal. 275(9). 2109–2121. 9 indexed citations
14.
Müller, Thomas, Sudip Roy, Wei Zhao, Astrid Maaß, & Dirk Reith. (2008). Economic simplex optimization for broad range property prediction: Strengths and weaknesses of an automated approach for tailoring of parameters. Fluid Phase Equilibria. 274(1-2). 27–35. 13 indexed citations
15.
Breton, Vincent, Martin Hofmann‐Apitius, Vinod Kasam, et al.. (2007). Virtual screening on large scale grids. Parallel Computing. 33(4-5). 289–301. 17 indexed citations
16.
Salzemann, Jean, Johan Montagnat, Astrid Maaß, et al.. (2007). Grid-enabled Virtual Screening Against Malaria. Journal of Grid Computing. 6(1). 29–43. 44 indexed citations
17.
Kasam, Vinod, Marc Zimmermann, Astrid Maaß, et al.. (2007). Design of New Plasmepsin Inhibitors: A Virtual High Throughput Screening Approach on the EGEE Grid.. ChemInform. 38(49). 7 indexed citations
18.
Salzemann, Jean, Matthieu Reichstadt, Marc Zimmermann, et al.. (2006). Demonstration of in silico docking at a large scale on grid infrastructure.. PubMed. 120. 155–7. 5 indexed citations
19.
Burbiel, Joachim C., et al.. (2003). Adenosine receptor agonists: from basic medicinal chemistry to clinical development. Expert Opinion on Emerging Drugs. 8(2). 537–576. 115 indexed citations
20.
Haverkort, Boudewijn R. & Astrid Maaß. (1993). Performability Modelling Using DyQNtool. University of Twente Research Information. 203(45). e93–e97. 5 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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