Norbert Furtmann

851 total citations
31 papers, 701 citations indexed

About

Norbert Furtmann is a scholar working on Molecular Biology, Organic Chemistry and Computational Theory and Mathematics. According to data from OpenAlex, Norbert Furtmann has authored 31 papers receiving a total of 701 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 10 papers in Organic Chemistry and 9 papers in Computational Theory and Mathematics. Recurrent topics in Norbert Furtmann's work include Computational Drug Discovery Methods (9 papers), Synthesis and biological activity (5 papers) and Protease and Inhibitor Mechanisms (4 papers). Norbert Furtmann is often cited by papers focused on Computational Drug Discovery Methods (9 papers), Synthesis and biological activity (5 papers) and Protease and Inhibitor Mechanisms (4 papers). Norbert Furtmann collaborates with scholars based in Germany, Pakistan and United States. Norbert Furtmann's co-authors include Jürgen Bajorath, Michael Gütschow, Ye Hu, Jamshed Iqbal, Abdul Hameed, Maxim Frizler, Friederike Lohr, Imtiaz Khan, Aamer Saeed and Marit Stirnberg and has published in prestigious journals such as Analytical Chemistry, The Journal of Physical Chemistry B and Journal of Bacteriology.

In The Last Decade

Norbert Furtmann

31 papers receiving 696 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Norbert Furtmann Germany 16 337 325 142 111 97 31 701
Hanan S. Anbar Egypt 16 272 0.8× 224 0.7× 49 0.3× 105 0.9× 47 0.5× 45 605
Henrik Möbitz Switzerland 17 551 1.6× 167 0.5× 162 1.1× 134 1.2× 79 0.8× 26 833
Narsimha Reddy Penthala United States 21 440 1.3× 578 1.8× 67 0.5× 99 0.9× 155 1.6× 85 1.1k
Halil I. Ciftci Japan 19 397 1.2× 500 1.5× 53 0.4× 109 1.0× 42 0.4× 51 922
Y. Amano Japan 18 474 1.4× 195 0.6× 114 0.8× 70 0.6× 108 1.1× 35 814
Nicole Caspers United States 15 490 1.5× 231 0.7× 116 0.8× 113 1.0× 87 0.9× 19 809
Zhuang Yang China 23 680 2.0× 680 2.1× 79 0.6× 253 2.3× 113 1.2× 61 1.3k
Chaya Duraiswami United States 11 534 1.6× 124 0.4× 296 2.1× 63 0.6× 50 0.5× 14 816
Tomomi Noguchi‐Yachide Japan 17 332 1.0× 208 0.6× 45 0.3× 109 1.0× 50 0.5× 36 631
Benjamin D. Horning United States 7 847 2.5× 656 2.0× 84 0.6× 250 2.3× 46 0.5× 7 1.2k

Countries citing papers authored by Norbert Furtmann

Since Specialization
Citations

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

Fields of papers citing papers by Norbert Furtmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Norbert Furtmann

This figure shows the co-authorship network connecting the top 25 collaborators of Norbert Furtmann. A scholar is included among the top collaborators of Norbert Furtmann 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 Norbert Furtmann. Norbert Furtmann 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.
Buchanan, Andrew, Eric M. Bennett, Andreas Evers, et al.. (2025). How to think about designing smart antibodies in the age of genAI: integrating biology, technology, and experience. mAbs. 17(1). 2490790–2490790. 3 indexed citations
2.
Starr, Charles G., et al.. (2024). Computational Screening for mAb Colloidal Stability with Coarse-Grained, Molecular-Scale Simulations. The Journal of Physical Chemistry B. 128(6). 1515–1526. 2 indexed citations
3.
Wossnig, Leonard, Norbert Furtmann, Andrew Buchanan, Sandeep Kumar, & Victor Greiff. (2024). Best practices for machine learning in antibody discovery and development. Drug Discovery Today. 29(7). 104025–104025. 9 indexed citations
4.
Schneider, Marion, Dilyana Dimova, Arnd Brandenburg, et al.. (2023). High-Throughput and Format-Agnostic Mispairing Assay for Multispecific Antibodies Using Intact Mass Spectrometry. Analytical Chemistry. 95(27). 10265–10278. 2 indexed citations
5.
Iqbal, Jamshed, Muhammad Salman Abbasi, Sumera Zaib, et al.. (2018). Identification of New Chromenone Derivatives as Cholinesterase Inhibitors and Molecular Docking Studies. Medicinal Chemistry. 14(8). 809–817. 1 indexed citations
6.
Furtmann, Norbert, et al.. (2016). En Route to New Therapeutic Options for Iron Overload Diseases: Matriptase‐2 as a Target for Kunitz‐Type Inhibitors. ChemBioChem. 17(7). 595–604. 22 indexed citations
7.
Khan, Imtiaz, Abdul Hameed, Aamer Saeed, et al.. (2016). Coumarin-thiazole and -oxadiazole derivatives: Synthesis, bioactivity and docking studies for aldose/aldehyde reductase inhibitors. Bioorganic Chemistry. 68. 177–186. 57 indexed citations
8.
Furtmann, Norbert, et al.. (2015). Active Site Mapping of Human Cathepsin F with Dipeptide Nitrile Inhibitors. ChemMedChem. 10(8). 1365–1377. 5 indexed citations
9.
Hameed, Abdul, Khalid Mohammed Khan, Zahid Shafiq, et al.. (2015). Synthesis, biological evaluation and molecular docking of N-phenyl thiosemicarbazones as urease inhibitors. Bioorganic Chemistry. 61. 51–57. 72 indexed citations
10.
Furtmann, Norbert, et al.. (2015). Limiting the Number of Potential Binding Modes by Introducing Symmetry into Ligands: Structure‐Based Design of Inhibitors for Trypsin‐Like Serine Proteases. Chemistry - A European Journal. 22(2). 610–625. 10 indexed citations
11.
Furtmann, Norbert & Jürgen Bajorath. (2015). Structural and Modeling Studies on ecto-5’-nucleotidase Aiding in Inhibitor Design. Mini-Reviews in Medicinal Chemistry. 15(1). 34–40. 6 indexed citations
12.
Gütschow, Michael, et al.. (2015). Oxidation of Disulfides to Taurine and Sulfanilic Acid Derivatives. Synthesis. 47(17). 2609–2616. 1 indexed citations
13.
Furtmann, Norbert, Ye Hu, Michael Gütschow, & Jürgen Bajorath. (2015). Identification of Interaction Hot Spots in Structures of Drug Targets on the Basis of Three‐Dimensional Activity Cliff Information. Chemical Biology & Drug Design. 86(6). 1458–1465. 8 indexed citations
14.
Aslam, Sana, Sumera Zaib, Matloob Ahmad, et al.. (2014). Novel structural hybrids of pyrazolobenzothiazines with benzimidazoles as cholinesterase inhibitors. European Journal of Medicinal Chemistry. 78. 106–117. 38 indexed citations
15.
16.
Horn, Martin, et al.. (2014). A Coumarin‐Labeled Vinyl Sulfone as Tripeptidomimetic Activity‐Based Probe for Cysteine Cathepsins. ChemBioChem. 15(7). 955–959. 46 indexed citations
17.
Furtmann, Norbert & Jürgen Bajorath. (2013). Evaluation of molecular model-based discovery of ecto-5′-nucleotidase inhibitors on the basis of X-ray structures. Bioorganic & Medicinal Chemistry. 21(21). 6616–6622. 7 indexed citations
18.
Wysocka, Magdalena, Michael Gütschow, Marit Stirnberg, et al.. (2013). Substrate specificity of human matriptase-2. Biochimie. 97. 121–127. 21 indexed citations
19.
Iqbal, Jamshed, Aamer Saeed, Rizwan Raza, et al.. (2013). Identification of sulfonic acids as efficient ecto-5′-nucleotidase inhibitors. European Journal of Medicinal Chemistry. 70. 685–691. 29 indexed citations
20.
Frizler, Maxim, et al.. (2010). Structural Optimization of Azadipeptide Nitriles Strongly Increases Association Rates and Allows the Development of Selective Cathepsin Inhibitors. Journal of Medicinal Chemistry. 54(1). 396–400. 71 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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