David E Malehorn

1.1k citations
19 papers · 824 indexed · h-index 14
Topics
Advanced Proteomics Techniques and Applications (6 papers)Machine Learning in Bioinformatics (3 papers)Metabolomics and Mass Spectrometry Studies (3 papers)

In The Last Decade

David E Malehorn

19 papers receiving 797 citations

Peers

David E Malehorn
Comparison fields: 5 of 88
  • Molecular Biology 533
  • Cell Biology 286
  • Plant Science 120
  • Surgery 79
  • Immunology 65
Replace Michael A. Hadders with:
Michael A. Hadders Netherlands
Akiyuki Hada Japan
Andrew P. VanDemark United States
Claire Gondeau France
Jonathan Low United States
Ramsey A. Saleem United States
Sudha Arya Canada
Marcel van Lith United Kingdom
Kaye D. Speicher United States
Götz Baumann Germany
David E Malehorn relative to Michael A. Hadders Netherlands Michael A. Hadders's profile →
Citations per field
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Citations per year

Countries citing papers authored by David E Malehorn

Since Specialization
Citations

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

Fields of papers citing papers by David E Malehorn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David E Malehorn. 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 David E Malehorn. The network helps show where David E Malehorn may publish in the future.

Co-authorship network of co-authors of David E Malehorn

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

All Works

19 of 19 papers shown
#WorkIndexed citations
1 21
2 21
3 12
4 20
5 13
6 39
7 36
8 30
9 23
10 8
11
Assessing the statistical significance of the achieved classification error of classifiers constructed using serum peptide profiles, and a prescription for random sampling repeated studies for massive high-throughput genomic and proteomic studies.
19
12 13
13 4
14 64
15 27
16 65
17 334
18 38
19 37

About David E Malehorn

David E Malehorn is a scholar working on Virology, Spectroscopy and Molecular Biology, having authored 19 papers that have together received 824 indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (6 papers), Machine Learning in Bioinformatics (3 papers) and Metabolomics and Mass Spectrometry Studies (3 papers). The work is most often cited by research in Cell Biology (286 citations), Virology (52 citations) and Transplantation (22 citations). David E Malehorn has collaborated with scholars based in United States, Australia and Canada. Frequent co-authors include Vytas A. Bankaitis, R. Greene, Scott D. Emr, William L. Bigbee, Dilip M. Shah, P.K.Y. Wong, P H Yuen, Jeffry R. Borgmeyer, Christine E. Smith and Ann E. Cleves. Their work appears in journals such as The Journal of Cell Biology, Bioinformatics and PLANT PHYSIOLOGY.

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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