Michael Hanke

683 total citations
47 papers, 491 citations indexed

About

Michael Hanke is a scholar working on Numerical Analysis, Computational Theory and Mathematics and Molecular Biology. According to data from OpenAlex, Michael Hanke has authored 47 papers receiving a total of 491 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Numerical Analysis, 18 papers in Computational Theory and Mathematics and 10 papers in Molecular Biology. Recurrent topics in Michael Hanke's work include Numerical methods for differential equations (22 papers), Matrix Theory and Algorithms (10 papers) and Advanced Numerical Methods in Computational Mathematics (6 papers). Michael Hanke is often cited by papers focused on Numerical methods for differential equations (22 papers), Matrix Theory and Algorithms (10 papers) and Advanced Numerical Methods in Computational Mathematics (6 papers). Michael Hanke collaborates with scholars based in Germany, Sweden and United States. Michael Hanke's co-authors include Pu Li, Roswitha März, Jens Pohl, Aideen M. Sullivan, Christina Sieber, Wiltrud Richter, Petra Knaus, Markus Kroeber, Wolfgang Poller and Haili Wang and has published in prestigious journals such as PLoS ONE, Neuroscience and Mathematics of Computation.

In The Last Decade

Michael Hanke

41 papers receiving 452 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Hanke Germany 11 161 119 102 73 60 47 491
Urszula Siedlecka United Kingdom 17 337 2.1× 31 0.3× 9 0.1× 7 0.1× 13 0.2× 66 1.0k
Tingting Wu China 10 20 0.1× 42 0.4× 26 0.3× 3 0.0× 117 1.9× 29 413
Daisuke Tominaga Japan 12 559 3.5× 6 0.1× 54 0.5× 35 0.5× 3 0.1× 35 814
Noriyuki Hori Japan 9 53 0.3× 12 0.1× 8 0.1× 133 1.8× 10 0.2× 46 324
Christopher L. Lee United States 10 169 1.0× 2 0.0× 10 0.1× 205 2.8× 132 2.2× 29 1.0k
H. Nishitani Japan 13 50 0.3× 4 0.0× 26 0.3× 96 1.3× 4 0.1× 62 651
Yao Zhao United States 9 13 0.1× 10 0.1× 11 0.1× 25 0.3× 19 0.3× 33 204
Robert Blake United States 8 93 0.6× 4 0.0× 7 0.1× 9 0.1× 30 0.5× 19 999
Songyan Wang China 13 93 0.6× 13 0.1× 122 1.7× 13 0.2× 59 457
Shin Usuki Japan 11 73 0.5× 2 0.0× 6 0.1× 8 0.1× 66 1.1× 69 470

Countries citing papers authored by Michael Hanke

Since Specialization
Citations

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

Fields of papers citing papers by Michael Hanke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Hanke

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Hanke. A scholar is included among the top collaborators of Michael Hanke 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 Michael Hanke. Michael Hanke 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.
2.
Hanke, Michael & Roswitha März. (2019). A reliable direct numerical treatment of differential–algebraic equations by overdetermined collocation: An operator approach. Journal of Computational and Applied Mathematics. 387. 112520–112520. 3 indexed citations
3.
Hanke, Michael, Roswitha März, & Caren Tischendorf. (2018). Least-squares collocation for higher-index linear differential-algebraic equations: Estimating the instability threshold. Mathematics of Computation. 88(318). 1647–1683. 5 indexed citations
4.
Djurfeldt, Mikael, et al.. (2017). Multirate method for co-simulation of electrical-chemical systems in multiscale modeling. Journal of Computational Neuroscience. 42(3). 245–256. 1 indexed citations
5.
Bhalla, Upinder S., et al.. (2016). Efficient Integration of Coupled Electrical-Chemical Systems in Multiscale Neuronal Simulations. Frontiers in Computational Neuroscience. 10. 97–97. 3 indexed citations
6.
Hanke, Michael, et al.. (2016). Least-squares collocation for linear higher-index differential–algebraic equations. Journal of Computational and Applied Mathematics. 317. 403–431. 12 indexed citations
7.
Hanke, Michael, et al.. (2013). Surface reactions on the cytoplasmatic membranes—Mathematical modeling of reaction and diffusion systems in a cell. Journal of Computational and Applied Mathematics. 262. 244–260. 5 indexed citations
8.
Dreij, Kristian, et al.. (2011). A Method for Efficient Calculation of Diffusion and Reactions of Lipophilic Compounds in Complex Cell Geometry. PLoS ONE. 6(8). e23128–e23128. 20 indexed citations
9.
Hanke, Michael, et al.. (2009). Simulation of Transport of Lipophilic Compounds in Complex Cell Geometry.
10.
Dupoirieux, L, Jens Pohl, Michael Hanke, & Didier Pourquier. (2008). A preliminary report on the effect of dimeric rhGDF-5 and its monomeric form rhGDF-5C465A on bone healing of rat cranial defects. Journal of Cranio-Maxillofacial Surgery. 37(1). 30–35. 15 indexed citations
11.
Hanke, Michael, et al.. (2005). Asymptotic properties of regularized differential-algebraic equations. edoc Publication server (Humboldt University of Berlin).
12.
Wang, Haili, et al.. (2004). Release of active and depot GDF-5 after adenovirus-mediated overexpression stimulates rabbit and human intervertebral disc cells. Journal of Molecular Medicine. 82(2). 126–134. 55 indexed citations
13.
Sammar, Marei, Sigmar Stricker, Georg C. Schwabe, et al.. (2004). Modulation of GDF5/BRI‐b signalling through interaction with the tyrosine kinase receptor Ror2. Genes to Cells. 9(12). 1227–1238. 85 indexed citations
14.
O’Keeffe, Gerard W., Michael Hanke, Jens Pohl, & Aideen M. Sullivan. (2004). Expression of growth differentiation factor-5 in the developing and adult rat brain. Developmental Brain Research. 151(1-2). 199–202. 27 indexed citations
15.
16.
Hanke, Michael & René Lamour. (2003). Consistent Initialization for Nonlinear Index-2 Differential–Algebraic Equation: Large Sparse Systems in MATLAB. Numerical Algorithms. 32(1). 67–85. 7 indexed citations
17.
Hanke, Michael, et al.. (2002). 28 Growth Differentiation Factor-5 (GDF-5) expression in the rat brain: developmental regulator, potential treatment?. PubMed. 201(5). 425–425. 1 indexed citations
18.
Hanke, Michael. (1994). Asymptotic Expansions for Regularization Methods of Linear Fully Implicit Differential-Algebraic Equations. Zeitschrift für Analysis und ihre Anwendungen. 13(3). 513–535. 4 indexed citations
19.
Hanke, Michael. (1989). Linear differential-algebraic equations in spaces of integrable functions. Journal of Differential Equations. 79(1). 14–30. 10 indexed citations
20.
Hanke, Michael, Roswitha März, & Andreas B. Neubauer. (1988). On the regularization of a class of nontransferable differential-algebraic equations. Journal of Differential Equations. 73(1). 119–132. 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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