Dan Sheppard

8 papers receiving 370 citations

Hit Papers

Ensembl variation resources 2018 · 309 citations
3092018202620202023100200300

Peers

Dan Sheppard
Comparison fields: 5 of 90
  • Aging 7
  • Cancer Research 58
  • Genetics 107
  • Molecular Biology 214
  • Human-Computer Interaction 16
Replace Andrew Parton with:
Andrew Parton United Kingdom
Mélissa Beaudoin Canada
Marc-Danie Nazaire United States
David Kunke Czechia
Michaela Willi United States
Oana Ursu United States
Pauline A. Fujita United States
David Lamparter Switzerland
Romain Groux Switzerland
D. Haussler United States
Dan Sheppard relative to Andrew Parton United Kingdom Andrew Parton's profile →
Citations per field
00.5×
Andrew Parton · 1×
Citations per year

Countries citing papers authored by Dan Sheppard

Since Specialization
Citations

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

Fields of papers citing papers by Dan Sheppard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dan Sheppard. 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 Dan Sheppard. The network helps show where Dan Sheppard may publish in the future.

Co-authors

The 25 scholars most cited alongside Dan Sheppard, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Dan Sheppard Line = papers co-authored together Dan Sheppard links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1
Ensembl variation resources
Hit paper breakdown →
2018309
2 201333
3 201315
4
Animated Paper Documents.
19978
5 19975
6
Paper Interfaces to the World-Wide Web.
19972
7 19972
8
Minibix: Item banking with web services
20081
9 19971
10 20110
11 20110

About Dan Sheppard

Dan Sheppard is a scholar working on Computer Science Applications, Human-Computer Interaction, Computer Vision and Pattern Recognition, Genetics and Sociology and Political Science, having authored 11 papers that have together received 376 indexed citations. Recurring topics across this work include Augmented Reality Applications (4 papers), Interactive and Immersive Displays (4 papers), Multimedia Communication and Technology (4 papers), Open Education and E-Learning (4 papers), Genomics and Phylogenetic Studies (2 papers), Pancreatic function and diabetes (1 paper), Genetic Mapping and Diversity in Plants and Animals (1 paper) and RNA and protein synthesis mechanisms (1 paper). The work is most often cited by research in Aging (7 citations), Cancer Research (58 citations), Genetics (107 citations), Molecular Biology (214 citations) and Human-Computer Interaction (16 citations). Dan Sheppard has collaborated with scholars based in United Kingdom. Frequent co-authors include Stephen J. Trevanion, Fiona Cunningham, Paul Flicek, William McLaren, Helen Schuilenburg, Anja Thormann, Irina M. Armean, Laurent Gil, Andrew Parton and Sarah Hunt. Their work appears in journals such as Computer Graphics Forum, Research in Learning Technology, Database, Nucleic Acids Research and ALT-J.

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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