Longlong Tu

750 citations
20 papers · 351 · 1 hit paper · h-index 10

Impact in

Papers in

Longlong Tu

18 papers receiving 342 citations

Longlong Tu's Hit Papers

Mechanisms of Chemotherapy-Induced Neurotoxicity 2022 · 131 citations
1310+1+2Years since publication4080120

Peers

Longlong Tu
Comparison fields: 5 of 93
  • Endocrine and Autonomic Systems 56
  • Sensory Systems 17
  • Neurology 28
  • Physiology 68
  • Biological Psychiatry 6
Replace Gang Tan with:
Gang Tan China
Consuelo Pascual Spain
Takayuki Ishida Japan
Christian Mésenge France
Michal Jurajda Czechia
Kirstin Reinecke Germany
Lukas Maurer Germany
José A. Pino Chile
Nicholas J. Hunt Australia
Takumi Ogawa Japan
Longlong Tu relative to Gang Tan China Gang Tan's profile →
Citations per field
00.5×3.3×
Gang Tan · 1×
Citations per year

Countries citing papers authored by Longlong Tu

Since Specialization
Citations

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

Fields of papers citing papers by Longlong Tu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1
Mechanisms of Chemotherapy-Induced Neurotoxicity
Hit paper breakdown →
2022131
2 202230
3 201726
4 202224
5 201722
6 201318
7 201816
8 202114
9 202114
10 20199
11 20218
12 20208
13 20206
14 20216
15 20186
16 20215
17 20245
18 20213
19 20240
20 20250

About Longlong Tu

Longlong Tu is a scholar working on Endocrine and Autonomic Systems, Molecular Biology, Cognitive Neuroscience, Reproductive Medicine and Surgery, having authored 20 papers that have together received 351 indexed citations. Recurring topics across this work include Regulation of Appetite and Obesity (7 papers), Hypothalamic control of reproductive hormones (3 papers), Acupuncture Treatment Research Studies (3 papers), Circadian rhythm and melatonin (3 papers), Sleep and Wakefulness Research (3 papers), Single-cell and spatial transcriptomics (2 papers), Eating Disorders and Behaviors (2 papers) and Molecular Biology Techniques and Applications (2 papers). The work is most often cited by research in Endocrine and Autonomic Systems (56 citations), Sensory Systems (17 citations), Neurology (28 citations), Physiology (68 citations) and Biological Psychiatry (6 citations). Longlong Tu has collaborated with scholars based in Hong Kong, United States and China. Frequent co-authors include John A. Rudd, Zengbing Lu, Julia Y.H. Liu, Halina Waś, Raquel Abalo, Ana Bagüés, Kulmira Nurgali, Yong Xu, Man P. Ngan and Qingchun Tong. Their work appears in journals such as Frontiers in Physiology, Frontiers in Pharmacology, Journal of Visualized Experiments, Endocrinology and Journal of Neuroscience.

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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