Spencer S. Ericksen

1.1k citations
29 papers · 681 indexed · h-index 15
Topics
Computational Drug Discovery Methods (11 papers)Machine Learning in Materials Science (6 papers)Neuroscience and Neuropharmacology Research (5 papers)

In The Last Decade

Spencer S. Ericksen

26 papers receiving 671 citations

Peers

Spencer S. Ericksen
Comparison fields: 5 of 92
  • Molecular Biology 399
  • Computational Theory and Mathematics 212
  • Pharmacology 187
  • Cellular and Molecular Neuroscience 86
  • Oncology 81
Replace Jennifer Venhorst with:
Jennifer Venhorst Netherlands
Munikumar Reddy Doddareddy South Korea
Sandrine Marchais‐Oberwinkler Germany
Franz Schuler Switzerland
Paul Weller United States
Carmela Gnerre Switzerland
Teresa Kaserer Austria
Hiroshi Kogen Japan
Upul K. Bandarage United States
Jichun Ma United States
Spencer S. Ericksen relative to Jennifer Venhorst Netherlands Jennifer Venhorst's profile →
Citations per field
00.5×1.7×
Jennifer Venhorst · 1×
Citations per year

Countries citing papers authored by Spencer S. Ericksen

Since Specialization
Citations

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

Fields of papers citing papers by Spencer S. Ericksen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Spencer S. Ericksen. 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 Spencer S. Ericksen. The network helps show where Spencer S. Ericksen may publish in the future.

Co-authorship network of co-authors of Spencer S. Ericksen

This figure shows the co-authorship network connecting the top 25 collaborators of Spencer S. Ericksen. A scholar is included among the top collaborators of Spencer S. Ericksen 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 Spencer S. Ericksen. Spencer S. Ericksen 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
#WorkIndexed citations
1 0
2 0
3 9
4 1
5 5
6 0
7 34
8 7
9 32
10 22
11 19
12 7
13 21
14 6
15 28
16 51
17 21
18 122
19 59
20 46

About Spencer S. Ericksen

Spencer S. Ericksen is a scholar working on Computational Theory and Mathematics, Toxicology and Pharmacology, having authored 29 papers that have together received 681 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (11 papers), Machine Learning in Materials Science (6 papers) and Neuroscience and Neuropharmacology Research (5 papers). The work is most often cited by research in Pharmacology (187 citations), Computational Theory and Mathematics (212 citations) and Biochemistry (78 citations). Spencer S. Ericksen has collaborated with scholars based in United States, Singapore and Belarus. Frequent co-authors include Grażyna D. Szklarz, Jianguo Liu, Charles Fisher, Scott A. Wildman, F. Michael Hoffmann, John A. Schetz, Dieter Schwarz, Horst Honeck, Wolf‐Hagen Schunck and Alexey Chernogolov. Their work appears in journals such as Nucleic Acids Research, Bioinformatics and Cancer Research.

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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