Daniel Weindl

2.1k total citations · 1 hit paper
25 papers, 1.2k citations indexed

About

Daniel Weindl is a scholar working on Molecular Biology, Spectroscopy and Control and Systems Engineering. According to data from OpenAlex, Daniel Weindl has authored 25 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 6 papers in Spectroscopy and 4 papers in Control and Systems Engineering. Recurrent topics in Daniel Weindl's work include Metabolomics and Mass Spectrometry Studies (10 papers), Gene Regulatory Network Analysis (10 papers) and Microbial Metabolic Engineering and Bioproduction (8 papers). Daniel Weindl is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (10 papers), Gene Regulatory Network Analysis (10 papers) and Microbial Metabolic Engineering and Bioproduction (8 papers). Daniel Weindl collaborates with scholars based in Germany, Luxembourg and United States. Daniel Weindl's co-authors include Karsten Hiller, Johannes Meiser, André Wegner, Jan Hasenauer, Fabian Fröhlich, Sean C. Sapcariu, Jenny Ghelfi, Leonard Schmiester, Tamara Kanashova and Julio R. Banga and has published in prestigious journals such as Nature Communications, Bioinformatics and PLoS ONE.

In The Last Decade

Daniel Weindl

24 papers receiving 1.2k citations

Hit Papers

Complexity of dopamine metabolism 2013 2026 2017 2021 2013 100 200 300 400
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. Complexity of dopamine metabolism
    2013 494 citations Johannes Meiser, Daniel Weindl et al. Cell Communication and Signaling profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Weindl Germany 16 685 172 119 99 87 25 1.2k
Ahmet Tarık Baykal Türkiye 24 827 1.2× 78 0.5× 210 1.8× 134 1.4× 332 3.8× 92 1.9k
Jacinth Naidoo United States 18 788 1.2× 234 1.4× 166 1.4× 45 0.5× 212 2.4× 22 1.7k
Lydie Nadal‐Desbarats France 27 801 1.2× 89 0.5× 283 2.4× 113 1.1× 197 2.3× 75 2.0k
Zhe Shi China 20 642 0.9× 123 0.7× 48 0.4× 30 0.3× 79 0.9× 56 1.3k
Tytus Bernaś Poland 24 907 1.3× 161 0.9× 56 0.5× 45 0.5× 132 1.5× 82 1.8k
Ju‐Young Lee South Korea 16 523 0.8× 81 0.5× 113 0.9× 49 0.5× 167 1.9× 40 1.3k
Steven Lynham United Kingdom 18 753 1.1× 80 0.5× 46 0.4× 91 0.9× 449 5.2× 49 1.4k
Maja Puchades Norway 22 830 1.2× 398 2.3× 123 1.0× 280 2.8× 434 5.0× 46 1.8k
Gretchen Lawler United States 7 810 1.2× 133 0.8× 138 1.2× 36 0.4× 158 1.8× 13 1.4k
Wenhua Zhang China 22 958 1.4× 456 2.7× 123 1.0× 49 0.5× 181 2.1× 43 1.9k

Countries citing papers authored by Daniel Weindl

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Weindl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Weindl

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Weindl. A scholar is included among the top collaborators of Daniel Weindl 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 Daniel Weindl. Daniel Weindl 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.
Lang, Paul, David R. Penas, Julio R. Banga, Daniel Weindl, & Béla Novák. (2024). Reusable rule-based cell cycle model explains compartment-resolved dynamics of 16 observables in RPE-1 cells. PLoS Computational Biology. 20(1). e1011151–e1011151. 2 indexed citations
2.
3.
Schälte, Yannik, Fabian Fröhlich, Dilan Pathirana, et al.. (2023). pyPESTO: a modular and scalable tool for parameter estimation for dynamic models. Bioinformatics. 39(11). 21 indexed citations
4.
Stapor, Paul, Stephan Grein, Dilan Pathirana, et al.. (2023). Efficient computation of adjoint sensitivities at steady-state in ODE models of biochemical reaction networks. PLoS Computational Biology. 19(1). e1010783–e1010783. 6 indexed citations
5.
Stapor, Paul, Leonard Schmiester, Christoph Wierling, et al.. (2022). Mini-batch optimization enables training of ODE models on large-scale datasets. Nature Communications. 13(1). 34–34. 19 indexed citations
6.
Schmiester, Leonard, Daniel Weindl, & Jan Hasenauer. (2021). Efficient gradient-based parameter estimation for dynamic models using qualitative data. Bioinformatics. 37(23). 4493–4500. 6 indexed citations
7.
Schmiester, Leonard, Daniel Weindl, & Jan Hasenauer. (2020). Parameterization of mechanistic models from qualitative data using an efficient optimal scaling approach. Journal of Mathematical Biology. 81(2). 603–623. 7 indexed citations
8.
Schmiester, Leonard, Yannik Schälte, Fabian Fröhlich, Jan Hasenauer, & Daniel Weindl. (2019). Efficient parameterization of large-scale dynamic models based on relative measurements. Bioinformatics. 36(2). 594–602. 23 indexed citations
9.
Villaverde, Alejandro F., Fabian Fröhlich, Daniel Weindl, Jan Hasenauer, & Julio R. Banga. (2018). Benchmarking optimization methods for parameter estimation in large kinetic models. Bioinformatics. 35(5). 830–838. 91 indexed citations
10.
Ostaszewski, Marek, Stephan Gebel, Inna Kuperstein, et al.. (2018). Community-driven roadmap for integrated disease maps. Briefings in Bioinformatics. 20(2). 659–670. 37 indexed citations
11.
Fröhlich, Fabian, T. Keßler, Daniel Weindl, et al.. (2018). Efficient Parameter Estimation Enables the Prediction of Drug Response Using a Mechanistic Pan-Cancer Pathway Model. Cell Systems. 7(6). 567–579.e6. 84 indexed citations
12.
Stapor, Paul, Daniel Weindl, Sabine Hug, et al.. (2017). PESTO: Parameter EStimation TOolbox. Bioinformatics. 34(4). 705–707. 62 indexed citations
13.
Weindl, Daniel, Thekla Cordes, Nadia Battello, et al.. (2016). Bridging the gap between non-targeted stable isotope labeling and metabolic flux analysis. Cancer & Metabolism. 4(1). 10–10. 27 indexed citations
14.
Weindl, Daniel, André Wegner, & Karsten Hiller. (2015). Non-targeted Tracer Fate Detection. Methods in enzymology on CD-ROM/Methods in enzymology. 561. 277–302. 13 indexed citations
15.
Weindl, Daniel, André Wegner, Christian Jäger, & Karsten Hiller. (2015). Isotopologue ratio normalization for non-targeted metabolomics. Journal of Chromatography A. 1389. 112–119. 20 indexed citations
16.
Weindl, Daniel, André Wegner, & Karsten Hiller. (2015). Metabolome-Wide Analysis of Stable Isotope Labeling—Is It Worth the Effort?. Frontiers in Physiology. 6. 344–344. 15 indexed citations
17.
Sapcariu, Sean C., Tamara Kanashova, Daniel Weindl, et al.. (2014). Simultaneous extraction of proteins and metabolites from cells in culture. MethodsX. 1. 74–80. 111 indexed citations
18.
Wegner, André, Johannes Meiser, Daniel Weindl, & Karsten Hiller. (2014). How metabolites modulate metabolic flux. Current Opinion in Biotechnology. 34. 16–22. 79 indexed citations
19.
Wegner, André, Daniel Weindl, Christian Jäger, et al.. (2014). Fragment Formula Calculator (FFC): Determination of Chemical Formulas for Fragment Ions in Mass Spectrometric Data. Analytical Chemistry. 86(4). 2221–2228. 22 indexed citations
20.
Meiser, Johannes, Daniel Weindl, & Karsten Hiller. (2013). Complexity of dopamine metabolism. Cell Communication and Signaling. 11(1). 34–34. 494 indexed citations breakdown →

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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