Hans van der Spek

1.6k total citations
23 papers, 1.3k citations indexed

About

Hans van der Spek is a scholar working on Molecular Biology, Epidemiology and Plant Science. According to data from OpenAlex, Hans van der Spek has authored 23 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 3 papers in Epidemiology and 3 papers in Plant Science. Recurrent topics in Hans van der Spek's work include Mitochondrial Function and Pathology (7 papers), Fungal and yeast genetics research (6 papers) and RNA and protein synthesis mechanisms (5 papers). Hans van der Spek is often cited by papers focused on Mitochondrial Function and Pathology (7 papers), Fungal and yeast genetics research (6 papers) and RNA and protein synthesis mechanisms (5 papers). Hans van der Spek collaborates with scholars based in Netherlands, United Kingdom and United States. Hans van der Spek's co-authors include Les Grivell, Marta Artal‐Sanz, Leo Nijtmans, Stanley Brul, J. van den Burg, Rob Benne, Paul Sloof, Leslie A. Grivell, M. Siep and Gert‐Jan Arts and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and The EMBO Journal.

In The Last Decade

Hans van der Spek

23 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hans van der Spek Netherlands 17 957 195 115 105 89 23 1.3k
R. Löwy France 15 327 0.3× 235 1.2× 140 1.2× 31 0.3× 51 0.6× 84 886
Christine B. Pearson United States 17 272 0.3× 77 0.4× 51 0.4× 67 0.6× 77 0.9× 22 742
Dongying Ma China 25 540 0.6× 79 0.4× 226 2.0× 40 0.4× 24 0.3× 46 1.4k
Jeffrey I. Gordon United States 10 911 1.0× 72 0.4× 183 1.6× 83 0.8× 135 1.5× 12 1.3k
Vladimir V. Gorn Russia 10 756 0.8× 147 0.8× 103 0.9× 84 0.8× 36 0.4× 28 1.2k
Fanyela Weinberg United States 8 1.1k 1.1× 84 0.4× 163 1.4× 169 1.6× 51 0.6× 10 1.4k
Gary S. Laco United States 21 856 0.9× 100 0.5× 56 0.5× 192 1.8× 15 0.2× 34 1.3k
Clémentine Wallet France 11 473 0.5× 52 0.3× 85 0.7× 140 1.3× 19 0.2× 18 808
Aikaterini Alexaki United States 15 487 0.5× 125 0.6× 83 0.7× 43 0.4× 46 0.5× 23 1.0k
Yoichi Robertus Fujii Japan 19 707 0.7× 146 0.7× 101 0.9× 52 0.5× 18 0.2× 61 1.4k

Countries citing papers authored by Hans van der Spek

Since Specialization
Citations

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

Fields of papers citing papers by Hans van der Spek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hans van der Spek. 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 Hans van der Spek. The network helps show where Hans van der Spek may publish in the future.

Co-authorship network of co-authors of Hans van der Spek

This figure shows the co-authorship network connecting the top 25 collaborators of Hans van der Spek. A scholar is included among the top collaborators of Hans van der Spek 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 Hans van der Spek. Hans van der Spek 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.
Smith, Reuben L., Martijs J. Jonker, Aldo Jongejan, et al.. (2017). Beyond the polymerase-γ theory: Production of ROS as a mode of NRTI-induced mitochondrial toxicity. PLoS ONE. 12(11). e0187424–e0187424. 28 indexed citations
2.
Smith, Reuben L., et al.. (2015). In Vivo Visualization and Quantification of Mitochondrial Morphology in C. elegans. Methods in molecular biology. 1265. 367–377. 3 indexed citations
3.
Boer, Richard de, et al.. (2015). Caenorhabditis elegans as a Model System for Studying Drug Induced Mitochondrial Toxicity. PLoS ONE. 10(5). e0126220–e0126220. 12 indexed citations
4.
Smith, Reuben L., Richard de Boer, Stanley Brul, Yelena V. Budovskaya, & Hans van der Spek. (2013). Premature and accelerated aging: HIV or HAART?. Frontiers in Genetics. 3. 328–328. 102 indexed citations
5.
Keijser, Bart J. F., Alex Ter Beek, Han Rauwerda, et al.. (2007). Analysis of Temporal Gene Expression duringBacillus subtilisSpore Germination and Outgrowth. Journal of Bacteriology. 189(9). 3624–3634. 99 indexed citations
6.
Brul, Stanley, Frank Schuren, R.C. Montijn, et al.. (2006). The impact of functional genomics on microbiological food quality and safety. International Journal of Food Microbiology. 112(3). 195–199. 15 indexed citations
7.
Lascaris, Romeo, Jan Piwowarski, Hans van der Spek, et al.. (2004). Overexpression of HAP4 in glucose-derepressed yeast cells reveals respiratory control of glucose-regulated genes. Microbiology. 150(4). 929–934. 19 indexed citations
8.
Reijans, Martin, Romeo Lascaris, Alexander Wittenberg, et al.. (2003). Quantitative comparison of cDNA-AFLP, microarrays, and genechip expression data in Saccharomyces cerevisiae. Genomics. 82(6). 606–618. 77 indexed citations
9.
Dziembowski, Andrzej, Jan Piwowarski, Michal Minczuk, et al.. (2003). The Yeast Mitochondrial Degradosome. Journal of Biological Chemistry. 278(3). 1603–1611. 128 indexed citations
10.
Artal‐Sanz, Marta, William Y.W. Tsang, Esther Willems, et al.. (2003). The Mitochondrial Prohibitin Complex Is Essential for Embryonic Viability and Germline Function in Caenorhabditis elegans. Journal of Biological Chemistry. 278(34). 32091–32099. 177 indexed citations
11.
Lascaris, Romeo, Harmen J. Bussemaker, André Boorsma, et al.. (2002). Hap4p overexpression in glucose-grown Saccharomyces cerevisiae induces cells to enter a novel metabolic state. Genome biology. 4(1). R3–R3. 85 indexed citations
12.
Back, Jaap Willem, Marta Artal‐Sanz, Luitzen de Jong, et al.. (2002). A structure for the yeast prohibitin complex: Structure prediction and evidence from chemical crosslinking and mass spectrometry. Protein Science. 11(10). 2471–2478. 144 indexed citations
13.
14.
Shah, Zahid H., et al.. (2000). The human homologue of the yeast mitochondrial AAA metalloprotease Yme1p complements a yeast yme1 disruptant. FEBS Letters. 478(3). 267–270. 40 indexed citations
15.
16.
Elzinga, S.D.J., et al.. (2000). Isolation and RNA-binding analysis of NAD+-isocitrate dehydrogenases from Kluyveromyces lactis and Schizosaccharomyces pombe. Current Genetics. 38(2). 87–94. 2 indexed citations
17.
Grivell, Leslie A., et al.. (1999). Mitochondrial assembly in yeast. FEBS Letters. 452(1-2). 57–60. 62 indexed citations
18.
Sloof, Paul, et al.. (1994). RNA editing in mitochondria of cultured trypanosomatids: Translatable mRNAs for NADH-dehydrogenase subunits are missing. Journal of Bioenergetics and Biomembranes. 26(2). 193–203. 16 indexed citations
19.
Spek, Hans van der, et al.. (1991). Conserved genes encode guide RNAs in mitochondria of Crithidia fasciculata.. The EMBO Journal. 10(5). 1217–1224. 72 indexed citations
20.
Spek, Hans van der, Gert‐Jan Arts, J. van den Burg, Paul Sloof, & Rob Benne. (1989). The nucleotide sequence of mitochondrial maxicircle genes ofCrithidia fasciculata. Nucleic Acids Research. 17(12). 4876–4876. 11 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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