Minya Lu

493 citations
17 papers · 159 · h-index 8

Impact in

Papers in

    • Antifungal resistance and susceptibility 5
    • SARS-CoV-2 and COVID-19 Research 3
    • COVID-19 Clinical Research Studies 2
    • Fungal Infections and Studies 4
    • Pneumonia and Respiratory Infections 2

Minya Lu

14 papers receiving 158 citations

Peers

Minya Lu
Comparison fields: 5 of 49
  • Infectious Diseases 109
  • Applied Microbiology and Biotechnology 6
  • Epidemiology 68
  • Clinical Biochemistry 11
  • Small Animals 10
Replace Xiudi Han with:
Xiudi Han China
Esma Eren Türkiye
José Arturo Martínez-Orozco Mexico
Philipp Köhler Germany
Luisa Durán Graeff Chile
Reham Khedr Egypt
Minh-Vu H Nguyen United States
Christoph Zurl Austria
Jessica S. Price United Kingdom
Lori Zapernick Canada
Minya Lu relative to Xiudi Han China Xiudi Han's profile →
Citations per field
00.5×1.5×
Xiudi Han · 1×
Citations per year

Countries citing papers authored by Minya Lu

Since Specialization
Citations

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

Fields of papers citing papers by Minya Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 202042
2 202237
3 202019
4 202111
5 201911
6 20219
7 20219
8 20207
9 20235
10 20203
11 20252
12 20222
13 20241
14 20251
15 20250
16 20250
17 20240

About Minya Lu

Minya Lu is a scholar working on Infectious Diseases, Epidemiology, Molecular Biology, Pulmonary and Respiratory Medicine and Molecular Medicine, having authored 17 papers that have together received 159 indexed citations. Recurring topics across this work include Antifungal resistance and susceptibility (5 papers), Fungal Infections and Studies (4 papers), Antibiotic Resistance in Bacteria (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers), Actinomycetales infections and treatment (2 papers), Antibiotics Pharmacokinetics and Efficacy (2 papers), COVID-19 Clinical Research Studies (2 papers) and Pneumonia and Respiratory Infections (2 papers). The work is most often cited by research in Infectious Diseases (109 citations), Applied Microbiology and Biotechnology (6 citations), Epidemiology (68 citations), Clinical Biochemistry (11 citations) and Small Animals (10 citations). Minya Lu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Xin Hou, Yingchun Xu, Meng Xu, Yingchun Xu, Te Liang, Hongye Wang, Xiaomei Zhang, Hu Duan, Meng Xiao and Xian Wu. Their work appears in journals such as Frontiers in Microbiology, Infection and Drug Resistance, BMJ Open, Aging and Molecular & Cellular Proteomics.

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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