Scott W. Van Arsdell

1.0k total citations
10 papers, 883 citations indexed

About

Scott W. Van Arsdell is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Scott W. Van Arsdell has authored 10 papers receiving a total of 883 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 1 paper in Oncology and 1 paper in Cell Biology. Recurrent topics in Scott W. Van Arsdell's work include RNA and protein synthesis mechanisms (7 papers), RNA Research and Splicing (6 papers) and RNA modifications and cancer (5 papers). Scott W. Van Arsdell is often cited by papers focused on RNA and protein synthesis mechanisms (7 papers), RNA Research and Splicing (6 papers) and RNA modifications and cancer (5 papers). Scott W. Van Arsdell collaborates with scholars based in United States and Netherlands. Scott W. Van Arsdell's co-authors include Alan M. Weiner, Tim Manser, R.F. Gesteland, Jeremy Thorner, Gary L. Stetler, M. D. Moody, S. F. Orencole, Chris Burns, Janice Pero and R. Rogers Yocum and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Scott W. Van Arsdell

10 papers receiving 804 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Scott W. Van Arsdell United States	9	760	160	85	57	49	10	883
Sarah L. Irons United Kingdom	11	539 0.7×	119 0.7×	29 0.3×	96 1.7×	73 1.5×	19	710
Keiko Mizuta Japan	20	918 1.2×	50 0.3×	90 1.1×	21 0.4×	138 2.8×	59	1.1k
Sophie Boguslawski United States	9	432 0.6×	43 0.3×	53 0.6×	23 0.4×	29 0.6×	12	545
Horst Hornig Germany	10	962 1.3×	52 0.3×	107 1.3×	55 1.0×	22 0.4×	12	1.1k
Masaru Ryoji United States	14	722 0.9×	97 0.6×	178 2.1×	33 0.6×	31 0.6×	23	895
Arndt Richter Germany	15	685 0.9×	88 0.6×	84 1.0×	16 0.3×	38 0.8×	26	758
Denise C. Krawitz United States	10	740 1.0×	92 0.6×	56 0.7×	172 3.0×	22 0.4×	10	788
Corinne C. Sherton United States	10	607 0.8×	40 0.3×	68 0.8×	31 0.5×	40 0.8×	10	748
Keith Verner United States	12	777 1.0×	50 0.3×	82 1.0×	13 0.2×	140 2.9×	18	913
M L Mace United States	10	345 0.5×	155 1.0×	129 1.5×	11 0.2×	43 0.9×	15	531

Countries citing papers authored by Scott W. Van Arsdell

Since Specialization

Citations

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

Fields of papers citing papers by Scott W. Van Arsdell

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Scott W. Van Arsdell. 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 Scott W. Van Arsdell. The network helps show where Scott W. Van Arsdell may publish in the future.

Co-authorship network of co-authors of Scott W. Van Arsdell

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

All Works

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10 of 10 papers shown

Arsdell, Scott W. Van, et al.. (2005). Removing a bottleneck in the Bacillus subtilis biotin pathway: BioA utilizes lysine rather than S‐adenosylmethionine as the amino donor in the KAPA‐to‐DAPA reaction. Biotechnology and Bioengineering. 91(1). 75–83. 37 indexed citations

Moody, M. D., et al.. (2001). Array-Based ELISAs for High-Throughput Analysis of Human Cytokines. BioTechniques. 31(1). 186–194. 151 indexed citations

Arsdell, Scott W. Van, et al.. (2000). Xplore ^® mRNA Assays for the Quantification of IL-1β and TNF-α mRNA in Lipopolysaccharide-Induced Mouse Macrophages. BioTechniques. 28(6). 1220–1225. 3 indexed citations

Arsdell, Scott W. Van, Gary L. Stetler, & Jeremy Thorner. (1987). The yeast repeated element sigma contains a hormone-inducible promoter.. Molecular and Cellular Biology. 7(2). 749–759. 29 indexed citations

Arsdell, Scott W. Van, Gary L. Stetler, & Jeremy Thorner. (1987). The Yeast Repeated Element Sigma Contains a Hormone-Inducible Promoter. Molecular and Cellular Biology. 7(2). 749–759. 74 indexed citations

Arsdell, Scott W. Van & Alan M. Weiner. (1984). Human Genes for U2 Small Nuclear RNA Are Tandemly Repeated. Molecular and Cellular Biology. 4(3). 492–499. 53 indexed citations

Arsdell, Scott W. Van & Alan M. Weiner. (1984). Pseudogenes for human U2 small nuclear RNA do not have a fixed site of 3′ truncation. Nucleic Acids Research. 12(3). 1463–1471. 39 indexed citations

Arsdell, Scott W. Van & Alan M. Weiner. (1984). Human genes for U2 small nuclear RNA are tandemly repeated.. Molecular and Cellular Biology. 4(3). 492–499. 105 indexed citations

Arsdell, Scott W. Van, et al.. (1981). Abundant pseudogenes for small nuclear RNAs are dispersed in the human genome.. Proceedings of the National Academy of Sciences. 78(2). 810–814. 113 indexed citations

10.

Arsdell, Scott W. Van, et al.. (1981). Direct repeats flank three small nuclear RNA pseudogenes in the human genome. Cell. 26(1). 11–17. 279 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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