C.A. Bucholtz

1.1k citations
20 papers · 911 indexed · 1 hit paper · h-index 8
Topics
Machine Learning in Bioinformatics (5 papers)Genomics and Phylogenetic Studies (4 papers)RNA and protein synthesis mechanisms (4 papers)
Partner nations
AustraliaUnited States

In The Last Decade

C.A. Bucholtz

19 papers receiving 813 citations

Hit Papers

The use of Coomassie Brilliant Blue G250 perchloric acid ...19752026199220091975100200300400500

Peers

C.A. Bucholtz
Comparison fields: 5 of 132
  • Molecular Biology 455
  • Computer Vision and Pattern Recognition 138
  • Genetics 94
  • Radiology, Nuclear Medicine and Imaging 84
  • Plant Science 76
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C.A. Bucholtz relative to Ryo Ito Japan Ryo Ito's profile →
Citations per field
00.5×9.5×
Ryo Ito · 1×
Citations per year

Countries citing papers authored by C.A. Bucholtz

Since Specialization
Citations

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

Fields of papers citing papers by C.A. Bucholtz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by C.A. Bucholtz. 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 C.A. Bucholtz. The network helps show where C.A. Bucholtz may publish in the future.

Co-authorship network of co-authors of C.A. Bucholtz

This figure shows the co-authorship network connecting the top 25 collaborators of C.A. Bucholtz. A scholar is included among the top collaborators of C.A. Bucholtz 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 C.A. Bucholtz. C.A. Bucholtz 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 4
2 39
3 6
4 1
5 213
6 9
7 0
8 4
9 2
10 12
11 14
12 2
13 5
14 24
15 3
16 7
17 6
18 4
19
The use of Coomassie Brilliant Blue G250 perchloric acid solution for staining in electrophoresis and isoelectric focusing on polyacrylamide gelsbreakdown →
550
20 6

About C.A. Bucholtz

C.A. Bucholtz is a scholar working on Computer Graphics and Computer-Aided Design, Sensory Systems and Molecular Biology, having authored 20 papers that have together received 911 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (5 papers), Genomics and Phylogenetic Studies (4 papers) and RNA and protein synthesis mechanisms (4 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (64 citations), Computer Vision and Pattern Recognition (138 citations) and Molecular Biology (455 citations). C.A. Bucholtz has collaborated with scholars based in Australia and United States. Frequent co-authors include A.H. Reisner, Gábor T. Herman, Jianmin Zheng, Ifor R. Beacham, Michael P. Jennings, Peter M. Power, Richard A. Jones, Dov Rosenfeld, Kwok‐Leung Tsui and J.H. Smelt. Their work appears in journals such as Nature, Nucleic Acids Research and The EMBO Journal.

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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