Nathan Good

1.7k citations
29 papers · 1.1k · h-index 18

Impact in

Papers in

Nathan Good

29 papers receiving 1.0k citations

Peers

Nathan Good
Comparison fields: 5 of 111
  • Human-Computer Interaction 87
  • Information Systems and Management 109
  • Geochemistry and Petrology 71
  • Biochemistry 87
  • Inorganic Chemistry 142
Replace Muhammad Ashraf Shaheen with:
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Rui Li China
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Citations per field
00.5×10×15×21.8×
Muhammad Ashraf Shaheen · 1×
Citations per year

Countries citing papers authored by Nathan Good

Since Specialization
Citations

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

Fields of papers citing papers by Nathan Good

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Nathan Good, 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 Nathan Good Line = papers co-authored together Nathan Good links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016138
2 2006109
3 2010105
4 2004101
5 201696
6 201175
7 201949
8 200946
9 202045
10 202037
11 200537
12 202225
13 201125
14 200621
15 202318
16 202417
17 201617
18 200717
19
TV-ACTA: Embedding an Activity-Centered Interface for Task Management in Email.
200712
20 202211

About Nathan Good

Nathan Good is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Inorganic Chemistry, Biochemistry and Information Systems, having authored 29 papers that have together received 1.1k indexed citations. Recurring topics across this work include Microbial metabolism and enzyme function (15 papers), Image Retrieval and Classification Techniques (5 papers), Microbial Metabolic Engineering and Bioproduction (5 papers), Advanced Image and Video Retrieval Techniques (5 papers), Metal-Catalyzed Oxygenation Mechanisms (4 papers), Metalloenzymes and iron-sulfur proteins (3 papers), Biochemical Acid Research Studies (3 papers) and Personal Information Management and User Behavior (2 papers). The work is most often cited by research in Human-Computer Interaction (87 citations), Information Systems and Management (109 citations), Geochemistry and Petrology (71 citations), Biochemistry (87 citations) and Inorganic Chemistry (142 citations). Nathan Good has collaborated with scholars based in United States, France and Singapore. Frequent co-authors include N. Cecilia Martínez-Gómez, Elizabeth Skovran, Huong N. Vu, Gabriel A. Subuyuj, Marc Davis, Simon King, Risto Sarvas, Diana K. Smetters, Seung-Taek Park and David M. Pennock. Their work appears in journals such as Journal of Bacteriology, JBIC Journal of Biological Inorganic Chemistry, PLoS ONE, Scientific Reports and Environmental Science & Technology.

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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