Hang Lu

172 papers receiving 6.4k citations

Hang Lu's Hit Papers

Pathogenic bacteria induce aversive olfactory learning in Caenorhabditis elegans 2005 · 607 citations
6070+7+14Years since publication200400600

Peers

Hang Lu
Comparison fields: 5 of 179
  • Aging 2.3k
  • Endocrine and Autonomic Systems 947
  • Cellular and Molecular Neuroscience 1.2k
  • Biophysics 341
  • Biomedical Engineering 2.3k
Replace Aravinthan D. T. Samuel with:
Aravinthan D. T. Samuel United States
Sreekanth H. Chalasani United States
Andrew Chisholm United States
Mei Zhen Canada
Miriam B. Goodman United States
Manuel Zimmer Austria
Rex Kerr United States
Yishi Jin United States
Evan Z. Macosko United States
Kang Shen United States
Hang Lu relative to Aravinthan D. T. Samuel United States Aravinthan D. T. Samuel's profile →
Citations per field
00.5×3.3×
Aravinthan D. T. Samuel · 1×
Citations per year

Countries citing papers authored by Hang Lu

Since Specialization
Citations

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

Fields of papers citing papers by Hang Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 179 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Pathogenic bacteria induce aversive olfactory learning in Caenorhabditis elegans
Hit paper breakdown →
2005607
2 2004446
3 2008290
4 2010263
5 2004251
6 2011168
7 2011126
8 2013125
9 2010124
10 2019119
11 2010107
12 2009100
13 201695
14 201391
15 201287
16 201687
17 201183
18 201083
19 201383
20 201378

About Hang Lu

Hang Lu is a scholar working on Aging, Molecular Biology, Biomedical Engineering, Cellular and Molecular Neuroscience and Physiology, having authored 179 papers that have together received 6.4k indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (71 papers), 3D Printing in Biomedical Research (44 papers), Photoreceptor and optogenetics research (24 papers), Microfluidic and Bio-sensing Technologies (21 papers), Circadian rhythm and melatonin (19 papers), Spaceflight effects on biology (17 papers), Cell Image Analysis Techniques (14 papers) and Microfluidic and Capillary Electrophoresis Applications (14 papers). The work is most often cited by research in Aging (2.3k citations), Endocrine and Autonomic Systems (947 citations), Cellular and Molecular Neuroscience (1.2k citations), Biophysics (341 citations) and Biomedical Engineering (2.3k citations). Hang Lu has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Cornelia I. Bargmann, Matthew M. Crane, Yun Zhang, Kwanghun Chung, Jeffrey N. Stirman, Catherine A. Rivet, Klavs F. Jensen, Martin A. Schmidt, Stanislav Y. Shvartsman and Mei Zhan. Their work appears in journals such as Lab on a Chip, eLife, Analytical Chemistry, Integrative Biology and PLoS ONE.

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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