Kaiyi Jiang

13 papers receiving 379 citations

Kaiyi Jiang's Hit Papers

Rapid in silico directed evolution by a protein language model with EVOLVEpro 2024 · 93 citations
930+1Years since publication255075

Peers

Kaiyi Jiang
Comparison fields: 5 of 75
  • Aging 10
  • Business and International Management 8
  • Biomaterials 45
  • Molecular Biology 214
  • Biomedical Engineering 79
Replace Bartłomiej Borek with:
Bartłomiej Borek Poland
Takahiro Otabe Japan
Chance M. Nowak United States
Diego S. D’Astolfo Argentina
Wenyuan Zhou United States
Tina Lebar Slovenia
Xueqing Li China
Timothy M. Wannier United States
Apresio Kefin Fajrial United States
Avi Jacob Israel
Kaiyi Jiang relative to Bartłomiej Borek Poland Bartłomiej Borek's profile →
Citations per field
00.5×11.7×
Bartłomiej Borek · 1×
Citations per year

Countries citing papers authored by Kaiyi Jiang

Since Specialization
Citations

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

Fields of papers citing papers by Kaiyi Jiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

14 of 14 papers shown
#Work
1
Rapid in silico directed evolution by a protein language model with EVOLVEpro
Hit paper breakdown →
202493
2 202260
3 202249
4 202338
5 202237
6 202132
7 202223
8 202514
9 202114
10 202312
11 202510
12 20252
13 20261
14 20250

About Kaiyi Jiang

Kaiyi Jiang is a scholar working on Molecular Biology, Biomaterials, Biomedical Engineering, Renewable Energy, Sustainability and the Environment and Condensed Matter Physics, having authored 14 papers that have together received 385 indexed citations. Recurring topics across this work include Nanoparticle-Based Drug Delivery (4 papers), CRISPR and Genetic Engineering (4 papers), RNA and protein synthesis mechanisms (4 papers), RNA regulation and disease (3 papers), Iron oxide chemistry and applications (2 papers), Characterization and Applications of Magnetic Nanoparticles (2 papers), Advanced Sensor and Control Systems (1 paper) and Graphene and Nanomaterials Applications (1 paper). The work is most often cited by research in Aging (10 citations), Business and International Management (8 citations), Biomaterials (45 citations), Molecular Biology (214 citations) and Biomedical Engineering (79 citations). Kaiyi Jiang has collaborated with scholars based in United States, Japan and China. Frequent co-authors include Omar O. Abudayyeh, Jonathan S. Gootenberg, Linlin Zhang, Gang Bao, Lukas Villiger, Alişan Kayabölen, Hiroshi Nishimasu, Qingbo Zhang, Masahiro Hiraizumi and Byungji Kim. Their work appears in journals such as Science, ACS Nano, Nature, Frontiers in Veterinary Science and Nature Materials.

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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