Yueheng Lan

2.5k citations
103 papers · 1.6k indexed · 1 hit paper · h-index 21

Yueheng Lan

91 papers receiving 1.5k citations

Hit Papers

Improved contact prediction in proteins: Using pseudolike...4382013202620172021100200300400

Peers

Yueheng Lan
Comparison fields: 5 of 107
  • Statistical and Nonlinear Physics 507
  • Atomic and Molecular Physics, and Optics 430
  • Molecular Biology 541
  • Modeling and Simulation 35
  • Computer Networks and Communications 166
Replace Anirvan M. Sengupta with:
Anirvan M. Sengupta India
Mark Paul United States
Luca Angelani Italy
Martin Bier United States
Benjamin B. Machta United States
Frédéric van Wijland France
Cyrill B. Muratov United States
Lendert Gelens Belgium
Javier Buceta Spain
Debashish Chowdhury India
Yueheng Lan relative to Anirvan M. Sengupta India Anirvan M. Sengupta's profile →
Citations per field
00.5×1.5×
Anirvan M. Sengupta · 1×
Citations per year

Countries citing papers authored by Yueheng Lan

Since Specialization
Citations

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

Fields of papers citing papers by Yueheng Lan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20260
2 20251
3 20251
4 20240
5 20241
6 20241
7 20241
8 20233
9 20234
10 20225
11 202110
12 20200
13 201919
14 201619
15 20164
16 20156
17 201226
18 20081
19 200875
20 200474

About Yueheng Lan

Yueheng Lan is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications and Atomic and Molecular Physics, and Optics, having authored 103 papers that have together received 1.6k indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (21 papers), Mechanical and Optical Resonators (20 papers), Gene Regulatory Network Analysis (13 papers), stochastic dynamics and bifurcation (13 papers), Advanced Thermodynamics and Statistical Mechanics (12 papers), Quantum chaos and dynamical systems (12 papers), Neural dynamics and brain function (9 papers) and Fluid Dynamics and Turbulent Flows (8 papers). The work is most often cited by research in Statistical and Nonlinear Physics (507 citations), Atomic and Molecular Physics, and Optics (430 citations) and Molecular Biology (541 citations). Yueheng Lan has collaborated with scholars based in China, United States and Sweden. Frequent co-authors include Erik Aurell, Magnus Ekeberg, Martin Weigt, Cecilia Lövkvist, Garegin A. Papoian, Wenjie Nie, Predrag Cvitanović, Igor Mezić, Aixi Chen and Shi‐Yao Zhu. Their work appears in journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and The Journal of Chemical Physics.

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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