Timon Schroeter

1.9k total citations
14 papers, 631 citations indexed

About

Timon Schroeter is a scholar working on Computational Theory and Mathematics, Molecular Biology and Spectroscopy. According to data from OpenAlex, Timon Schroeter has authored 14 papers receiving a total of 631 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computational Theory and Mathematics, 7 papers in Molecular Biology and 6 papers in Spectroscopy. Recurrent topics in Timon Schroeter's work include Computational Drug Discovery Methods (9 papers), Analytical Chemistry and Chromatography (6 papers) and Machine Learning in Materials Science (5 papers). Timon Schroeter is often cited by papers focused on Computational Drug Discovery Methods (9 papers), Analytical Chemistry and Chromatography (6 papers) and Machine Learning in Materials Science (5 papers). Timon Schroeter collaborates with scholars based in Germany, United States and Switzerland. Timon Schroeter's co-authors include Klaus‐Robert Müller, Sebastian Mika, Antonius ter Laak, Nikolaus Heinrich, Katja Hansen, Andreas Sutter, Thomas Steger‐Hartmann, Anton Schwaighofer, Detlev Suelzle and Matthias Rupp and has published in prestigious journals such as Journal of Chemical Information and Modeling, Molecular Pharmaceutics and Bioorganic & Medicinal Chemistry Letters.

In The Last Decade

Timon Schroeter

14 papers receiving 604 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Timon Schroeter Germany	12	466	265	188	103	69	14	631
Qian Xie United States	7	424 0.9×	234 0.9×	91 0.5×	86 0.8×	28 0.4×	10	688
Iurii Sushko Germany	6	523 1.1×	265 1.0×	177 0.9×	102 1.0×	62 0.9×	13	709
Jeroen Kazius Netherlands	4	315 0.7×	202 0.8×	68 0.4×	72 0.7×	42 0.6×	4	551
Vishal B. Siramshetty United States	16	488 1.0×	443 1.7×	88 0.5×	44 0.4×	67 1.0×	24	848
Arwa Bin Raies Saudi Arabia	9	340 0.7×	297 1.1×	119 0.6×	28 0.3×	58 0.8×	11	722
Patrícia R. Oliveira Brazil	9	386 0.8×	302 1.1×	125 0.7×	40 0.4×	32 0.5×	24	591
Suman Chakravarti United States	12	278 0.6×	171 0.6×	70 0.4×	62 0.6×	35 0.5×	26	494
Stephen J. Barigye Spain	19	636 1.4×	477 1.8×	169 0.9×	181 1.8×	54 0.8×	78	1.1k
Oliver Horlacher Switzerland	8	583 1.3×	680 2.6×	159 0.8×	239 2.3×	92 1.3×	10	1.1k
Steven M. Muskal United States	9	437 0.9×	531 2.0×	154 0.8×	146 1.4×	66 1.0×	16	820

Countries citing papers authored by Timon Schroeter

Since Specialization

Citations

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

Fields of papers citing papers by Timon Schroeter

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Timon Schroeter

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

All Works

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14 of 14 papers shown

1.

Hansen, Katja, David Baehrens, Timon Schroeter, Matthias Rupp, & Klaus‐Robert Müller. (2011). Visual Interpretation of Kernel‐Based Prediction Models. Molecular Informatics. 30(9). 817–826. 36 indexed citations

2.

Rupp, Matthias, Ewgenij Proschak, Timon Schroeter, et al.. (2010). Truxillic acid derivatives act as peroxisome proliferator-activated receptor γ activators. Bioorganic & Medicinal Chemistry Letters. 20(9). 2920–2923. 11 indexed citations

3.

Rupp, Matthias, Timon Schroeter, Heiko Zettl, et al.. (2009). From Machine Learning to Natural Product Derivatives that Selectively Activate Transcription Factor PPARγ. ChemMedChem. 5(2). 191–194. 45 indexed citations

4.

Schwaighofer, Anton, Timon Schroeter, Sebastian Mika, & Gilles Blanchard. (2009). How Wrong Can We Get? A Review of Machine Learning Approaches and Error Bars. Combinatorial Chemistry & High Throughput Screening. 12(5). 453–468. 23 indexed citations

5.

Hansen, Katja, Sebastian Mika, Timon Schroeter, et al.. (2009). Benchmark Data Set for in Silico Prediction of Ames Mutagenicity. Journal of Chemical Information and Modeling. 49(9). 2077–2081. 257 indexed citations

6.

Hansen, Katja, Timon Schroeter, Georg Rast, et al.. (2009). Bias-Correction of Regression Models: A Case Study on hERG Inhibition. Journal of Chemical Information and Modeling. 49(6). 1486–1496. 22 indexed citations

7.

Hansen, Katja, Mika Sirén, Timon Schroeter, et al.. (2009). A benchmark data set for in silico prediction of ames mutagenicity. Chemistry Central Journal. 3(S1). 21 indexed citations

8.

Schwaighofer, Anton, Timon Schroeter, Sebastian Mika, et al.. (2008). A Probabilistic Approach to Classifying Metabolic Stability. Journal of Chemical Information and Modeling. 48(4). 785–796. 28 indexed citations

9.

Schroeter, Timon, Anton Schwaighofer, Sebastian Mika, et al.. (2007). Predicting Lipophilicity of Drug‐Discovery Molecules using Gaussian Process Models. ChemMedChem. 2(9). 1265–1267. 22 indexed citations

10.

Schroeter, Timon, Anton Schwaighofer, Sebastian Mika, et al.. (2007). Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules. Journal of Computer-Aided Molecular Design. 21(9). 485–498. 51 indexed citations

11.

Schroeter, Timon, Anton Schwaighofer, Sebastian Mika, et al.. (2007). Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules. Journal of Computer-Aided Molecular Design. 21(12). 651–664. 35 indexed citations

12.

Schroeter, Timon, Anton Schwaighofer, Sebastian Mika, et al.. (2007). Machine Learning Models for Lipophilicity and Their Domain of Applicability. Molecular Pharmaceutics. 4(4). 524–538. 23 indexed citations

13.

Schwaighofer, Anton, Timon Schroeter, Sebastian Mika, et al.. (2007). Accurate Solubility Prediction with Error Bars for Electrolytes: A Machine Learning Approach. Journal of Chemical Information and Modeling. 47(2). 407–424. 56 indexed citations

14.

Kroll, Peter, Timon Schroeter, & Martina Peters. (2005). Prediction of Novel Phases of Tantalum(V) Nitride and Tungsten(VI) Nitride that Can Be Synthesized under High Pressure and High Temperature.. ChemInform. 36(41). 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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