Sverker Holmgren

680 total citations
54 papers, 415 citations indexed

About

Sverker Holmgren is a scholar working on Computer Networks and Communications, Numerical Analysis and Computational Mechanics. According to data from OpenAlex, Sverker Holmgren has authored 54 papers receiving a total of 415 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Networks and Communications, 14 papers in Numerical Analysis and 13 papers in Computational Mechanics. Recurrent topics in Sverker Holmgren's work include Advanced Numerical Methods in Computational Mathematics (13 papers), Genetic Mapping and Diversity in Plants and Animals (11 papers) and Numerical methods for differential equations (11 papers). Sverker Holmgren is often cited by papers focused on Advanced Numerical Methods in Computational Mathematics (13 papers), Genetic Mapping and Diversity in Plants and Animals (11 papers) and Numerical methods for differential equations (11 papers). Sverker Holmgren collaborates with scholars based in Sweden, United States and Portugal. Sverker Holmgren's co-authors include Hans Karlsson, Örjan Carlborg, Katharina Kormann, Salman Toor, Elisabeth Larsson, Erik Hägersten, Michael Thuné, Lars Rönnegård, Ebba Þóra Hvannberg and Stefano Serra‐Capizzano and has published in prestigious journals such as The Journal of Chemical Physics, Bioinformatics and Genetics.

In The Last Decade

Sverker Holmgren

51 papers receiving 375 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sverker Holmgren Sweden 11 102 99 91 89 80 54 415
Glenn R. Luecke United States 13 66 0.6× 8 0.1× 134 1.5× 40 0.4× 11 0.1× 48 512
Andrés E. Tomás Spain 9 74 0.7× 25 0.3× 59 0.6× 33 0.4× 13 0.2× 34 234
Field G. Zee United States 12 146 1.4× 31 0.3× 371 4.1× 31 0.3× 11 0.1× 21 662
Prasoon Tiwari United States 12 279 2.7× 14 0.1× 183 2.0× 17 0.2× 14 0.2× 25 597
Hayato Goto Japan 18 158 1.5× 7 0.1× 91 1.0× 647 7.3× 7 0.1× 69 1.4k
Eloy Romero United States 11 27 0.3× 16 0.2× 79 0.9× 24 0.3× 10 0.1× 20 328
D. Noutsos Greece 11 355 3.5× 50 0.5× 39 0.4× 114 1.3× 184 2.3× 46 481
Marko Budinich Italy 7 108 1.1× 17 0.2× 53 0.6× 6 0.1× 17 0.2× 28 341
Dima Grigoriev France 12 377 3.7× 30 0.3× 47 0.5× 7 0.1× 30 0.4× 71 564
P. J. Eberlein United States 11 248 2.4× 15 0.2× 58 0.6× 53 0.6× 118 1.5× 20 354

Countries citing papers authored by Sverker Holmgren

Since Specialization
Citations

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

Fields of papers citing papers by Sverker Holmgren

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sverker Holmgren

This figure shows the co-authorship network connecting the top 25 collaborators of Sverker Holmgren. A scholar is included among the top collaborators of Sverker Holmgren 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 Sverker Holmgren. Sverker Holmgren 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.
Mahjani, Behrang, Salman Toor, Carl Nettelblad, & Sverker Holmgren. (2016). A Flexible Computational Framework Using R and Map-Reduce for Permutation Tests of Massive Genetic Analysis of Complex Traits. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 14(2). 381–392. 1 indexed citations
2.
Holmgren, Sverker, et al.. (2014). Impact of Code Refactoring Using Object-Oriented Methodology on a Scientific Computing Application. 125–134. 13 indexed citations
3.
Nettelblad, Carl, Behrang Mahjani, & Sverker Holmgren. (2013). Fast and Accurate Detection of Multiple Quantitative Trait Loci. Journal of Computational Biology. 20(9). 687–702. 2 indexed citations
4.
Toor, Salman, et al.. (2013). Scientific Analysis by Queries in Extended SPARQL over a Scalable e-Science Data Store. 98–106. 5 indexed citations
5.
Östberg, Per-Olov, Andreas Hellander, Brian Drawert, et al.. (2012). Reducing Complexity in Management of eScience Computations. 35. 845–852. 7 indexed citations
6.
Gustafsson, Magnus, James Demmel, & Sverker Holmgren. (2012). Numerical evaluation of the Communication-Avoiding Lanczos algorithm. KTH Publication Database DiVA (KTH Royal Institute of Technology). 3 indexed citations
7.
Toor, Salman, et al.. (2011). A Scalable Architecture for e-Science Data Management. 210–217. 2 indexed citations
8.
Hägersten, Erik, et al.. (2009). Reconsidering algorithms for iterative solvers in the multicore era. International Journal of Computational Science and Engineering. 4(4). 270–282. 1 indexed citations
9.
Rönnegård, Lars, et al.. (2009). Assessing a multiple QTL search using the variance component model. Computational Biology and Chemistry. 34(1). 34–41. 1 indexed citations
10.
Holmgren, Sverker, et al.. (2008). Efficient optimization algorithms and implementations for genetic analysis of complex traits on a grid system with multicore nodes. 2 indexed citations
11.
Holmgren, Sverker, et al.. (2008). Newton-type methods for REML estimation in genetic analysis of quantitative traits. Journal of Computational Methods in Sciences and Engineering. 8(1-2). 53–67. 3 indexed citations
12.
Holmgren, Sverker, et al.. (2007). Grid-Enabling an Efficient Algorithm for Demanding Global Optimization Problems in Genetic Analysis. 138. 205–212. 3 indexed citations
13.
Holmgren, Sverker, et al.. (2005). Discrete Fundamental Solution Preconditioning for Hyperbolic Systems of PDE. Journal of Scientific Computing. 30(1). 35–60. 2 indexed citations
14.
Holmgren, Sverker, et al.. (2004). Simultaneous search for multiple QTL using the global optimization algorithm DIRECT. Bioinformatics. 20(12). 1887–1895. 51 indexed citations
15.
Holmgren, Sverker, Christer Peterson, & Hans Karlsson. (2004). Time-marching methods for the time-dependent Schrödinger equation. 53–56. 1 indexed citations
16.
Holmgren, Sverker, et al.. (2003). Convergence acceleration for the steady-state Euler equations. Computers & Fluids. 32(8). 1075–1092. 2 indexed citations
17.
Karlsson, Hans & Sverker Holmgren. (2002). Cross correlation functions Cnm(E) via Lanczos algorithms without diagonalization. The Journal of Chemical Physics. 117(20). 9116–9123. 14 indexed citations
18.
Holmgren, Sverker, et al.. (1996). Semicirculant Solvers and Boundary Corrections for First-Order Partial Differential Equations. SIAM Journal on Scientific Computing. 17(3). 613–630. 10 indexed citations
19.
Holmgren, Sverker, et al.. (1994). Semicirculant Preconditioners for First-Order Partial Differential Equations. SIAM Journal on Scientific Computing. 15(2). 385–407. 16 indexed citations
20.
Holmgren, Sverker, et al.. (1992). Iterative Solution Methods and Preconditioners for Block-Tridiagonal Systems of Equations. SIAM Journal on Matrix Analysis and Applications. 13(3). 863–886. 34 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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