Tyr Wiesner‐Hanks

1.7k citations
14 papers · 1.2k indexed · 2 hit papers · h-index 13
Topics
Smart Agriculture and AI (5 papers)Remote Sensing in Agriculture (4 papers)Plant Pathogens and Fungal Diseases (4 papers)

In The Last Decade

Tyr Wiesner‐Hanks

14 papers receiving 1.2k citations

Hit Papers

Navigating complexity to breed disease-resistant crops201720262020202320172017100200300

Peers

Tyr Wiesner‐Hanks
Comparison fields: 5 of 86
  • Plant Science 1.1k
  • Ecology 253
  • Analytical Chemistry 238
  • Molecular Biology 156
  • Genetics 152
Replace Rebecca Bart with:
Rebecca Bart United States
Cory D. Hirsch United States
Yosuke Yoshioka Japan
Д. А. Афонников Russia
Ethan L. Stewart United States
Jinliang Yang United States
Jiaoping Zhang United States
Hervé Goëau France
Takanari Tanabata Japan
Richard J. Harrison United Kingdom
Tyr Wiesner‐Hanks relative to Rebecca Bart United States Rebecca Bart's profile →
Citations per field
00.5×3.4×
Rebecca Bart · 1×
Citations per year

Countries citing papers authored by Tyr Wiesner‐Hanks

Since Specialization
Citations

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

Fields of papers citing papers by Tyr Wiesner‐Hanks

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tyr Wiesner‐Hanks. 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 Tyr Wiesner‐Hanks. The network helps show where Tyr Wiesner‐Hanks may publish in the future.

Co-authorship network of co-authors of Tyr Wiesner‐Hanks

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

All Works

14 of 14 papers shown
#WorkIndexed citations
1 2
2 19
3 75
4 89
5 87
6 122
7 13
8
Navigating complexity to breed disease-resistant cropsbreakdown →
340
9 15
10
Automated Identification of Northern Leaf Blight-Infected Maize Plants from Field Imagery Using Deep Learningbreakdown →
305
11 15
12 106
13 31
14 18

About Tyr Wiesner‐Hanks

Tyr Wiesner‐Hanks is a scholar working on Geography, Planning and Development, Plant Science and Cell Biology, having authored 14 papers that have together received 1.2k indexed citations. Recurring topics across this work include Smart Agriculture and AI (5 papers), Remote Sensing in Agriculture (4 papers) and Plant Pathogens and Fungal Diseases (4 papers). The work is most often cited by research in Plant Science (1.1k citations), Analytical Chemistry (238 citations) and Ecology (253 citations). Tyr Wiesner‐Hanks has collaborated with scholars based in United States, Australia and Chile. Frequent co-authors include Rebecca Nelson, Peter Balint‐Kurti, Ethan L. Stewart, Chad DeChant, Michael A. Gore, Hod Lipson, Randall J. Wisser, Nicholas Kaczmar, Harvey Wu and Siyuan Chen. Their work appears in journals such as Nature Reviews Genetics, Frontiers in Plant Science and Annual Review of Phytopathology.

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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