David W. Kane

4.8k citations
18 papers · 2.4k indexed · 1 hit paper · h-index 15
Topics
Gene expression and cancer classification (9 papers)Bioinformatics and Genomic Networks (8 papers)Software Engineering Techniques and Practices (4 papers)

In The Last Decade

David W. Kane

18 papers receiving 2.4k citations

Hit Papers

GoMiner: a resource for biological interpretation of geno...20032026201020182003250500750

Peers

David W. Kane
Comparison fields: 5 of 143
  • Molecular Biology 1.8k
  • Cancer Research 315
  • Oncology 184
  • Genetics 183
  • Pulmonary and Respiratory Medicine 154
Replace D. B. Troup with:
D. B. Troup United States
Uğis Sarkans United Kingdom
B. F. Francis Ouellette Canada
Alan J. Robinson United Kingdom
Amelia Ireland United Kingdom
C. Evangelista United States
S. E. Wilhite United States
Carolina Perez‐Iratxeta Canada
Barry R. Zeebèrg United States
Carl F. Schaefer United States
David W. Kane relative to D. B. Troup United States D. B. Troup's profile →
Citations per field
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D. B. Troup · 1×
Citations per year

Countries citing papers authored by David W. Kane

Since Specialization
Citations

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

Fields of papers citing papers by David W. Kane

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David W. Kane

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

All Works

18 of 18 papers shown
#WorkIndexed citations
1 26
2 278
3 83
4
Software Architecture: Organizational Principles and Patterns
16
5 14
6 58
7 23
8 38
9 390
10 229
11 12
12 64
13 129
14
GoMiner: a resource for biological interpretation of genomic and proteomic databreakdown →
963
15 17
16 37
17
Development of gene ontology tool for biological interpretation of genomic and proteomic data.
13
18 57

About David W. Kane

David W. Kane is a scholar working on Statistics and Probability, Molecular Biology and Human-Computer Interaction, having authored 18 papers that have together received 2.4k indexed citations. Recurring topics across this work include Gene expression and cancer classification (9 papers), Bioinformatics and Genomic Networks (8 papers) and Software Engineering Techniques and Practices (4 papers). The work is most often cited by research in Molecular Biology (1.8k citations), Cancer Research (315 citations) and Aging (29 citations). David W. Kane has collaborated with scholars based in United States, Netherlands and Germany. Frequent co-authors include John N. Weinstein, Barry R. Zeebèrg, Margot Sunshine, William C. Reinhold, Kimberly J. Bussey, Joseph Riss, J. Carl Barrett, May D. Wang, Samir Lababidi and Weimin Feng. Their work appears in journals such as Nature Genetics, 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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