B.J. Kim

19 papers receiving 1.3k citations

Hit Papers

Rapid in silico directed evolution by a protein language model with EVOLVEpro 2024 · 73 citations
732018202620202023100200300

Peers

B.J. Kim
Comparison fields: 5 of 112
  • Biomaterials 211
  • Microbiology 90
  • Molecular Biology 750
  • Biomedical Engineering 423
  • Pharmaceutical Science 53
Replace Guangchao Qing with:
Guangchao Qing China
Jieming Li China
Xi Zhu China
Jie Liang China
Shann S. Yu United States
Zhaoting Li China
Haifeng Sun China
Zhidong Zhou United States
Davoud Ahmadvand Iran
B.J. Kim relative to Guangchao Qing China Guangchao Qing's profile →
Citations per field
00.5×10×20×30.3×
Guangchao Qing · 1×
Citations per year

Countries citing papers authored by B.J. Kim

Since Specialization
Citations

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

Fields of papers citing papers by B.J. Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by B.J. Kim. 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 B.J. Kim. The network helps show where B.J. Kim may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Antibiotic-loaded nanoparticles targeted to the site of infection enhance antibacterial efficacy
Hit paper breakdown →
2018328
2 2019247
3 2018153
4 2015143
5 201988
6 202286
7
Rapid in silico directed evolution by a protein language model with EVOLVEpro
Hit paper breakdown →
202473
8 201435
9 202325
10 202123
11 201922
12 202021
13 202311
14 20239
15 20248
16 20194
17 20124
18 20243
19 20192
20 20250

About B.J. Kim

B.J. Kim is a scholar working on Endocrinology, Immunology, Molecular Biology, Microbiology and Ecology, having authored 22 papers that have together received 1.3k indexed citations. Recurring topics across this work include RNA Interference and Gene Delivery (9 papers), Immunotherapy and Immune Responses (7 papers), Advanced biosensing and bioanalysis techniques (6 papers), Nanoplatforms for cancer theranostics (5 papers), Bacteriophages and microbial interactions (4 papers), Silicon Nanostructures and Photoluminescence (3 papers), CAR-T cell therapy research (2 papers) and Cancer Immunotherapy and Biomarkers (2 papers). The work is most often cited by research in Biomaterials (211 citations), Microbiology (90 citations), Molecular Biology (750 citations), Biomedical Engineering (423 citations) and Pharmaceutical Science (53 citations). B.J. Kim has collaborated with scholars based in United States, South Korea and Australia. Frequent co-authors include Michael J. Sailor, Ji‐Ho Park, Erkki Ruoslahti, Jinyoung Kang, Hong‐Bo Pang, Aman P. Mann, Gary B. Braun, Tambet Teesalu, Sazid Hussain and Tarmo Mölder. Their work appears in journals such as Advanced Materials, Journal of Visualized Experiments, Nano Letters, ACS Biomaterials Science & Engineering and eLife.

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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