Lan Huang

421 citations
12 papers · 247 · h-index 5

Impact in

    • Cellular transport and secretion
    • Endoplasmic Reticulum Stress and Disease
    • Protein Kinase Regulation and GTPase Signaling
    • Protein Structure and Dynamics
    • Cell death mechanisms and regulation
    • PI3K/AKT/mTOR signaling in cancer
    • Melanoma and MAPK Pathways

Papers in

Lan Huang

11 papers receiving 241 citations

Peers

Lan Huang
Comparison fields: 5 of 56
  • Cell Biology 58
  • Molecular Biology 198
  • Immunology and Allergy 10
  • Cellular and Molecular Neuroscience 16
  • Materials Chemistry 40
Replace Deepak Kolippakkam with:
Deepak Kolippakkam United States
A. I. Kornelyuk Ukraine
Marine Dumousseau United Kingdom
Yuxiao Wang China
Hajime Nagashima Japan
Jui‐Hung Weng United States
Mengting Gu China
André Gohr Germany
Sayantan Mitra India
Zuhair Iftikhar Finland
Lan Huang relative to Deepak Kolippakkam United States Deepak Kolippakkam's profile →
Citations per field
00.5×
Deepak Kolippakkam · 1×
Citations per year

Countries citing papers authored by Lan Huang

Since Specialization
Citations

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

Fields of papers citing papers by Lan Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Lan Huang, 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 Lan Huang Line = papers co-authored together Lan Huang links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 1998215
2 20128
3 20096
4 20196
5 20084
6 20092
7 20082
8 20201
9 20141
10 20191
11 20151
12
Improved particle swarm optimization algorithm for Rectangular Cutting-Stock Problem
20100

About Lan Huang

Lan Huang is a scholar working on Information Systems, Computer Networks and Communications, Statistical and Nonlinear Physics, Artificial Intelligence and Electrical and Electronic Engineering, having authored 12 papers that have together received 247 indexed citations. Recurring topics across this work include Optimization and Packing Problems (2 papers), Advanced Manufacturing and Logistics Optimization (2 papers), Complex Network Analysis Techniques (2 papers), Network Security and Intrusion Detection (2 papers), Vehicle Routing Optimization Methods (1 paper), Spam and Phishing Detection (1 paper), Online Learning and Analytics (1 paper) and Advanced Wireless Network Optimization (1 paper). The work is most often cited by research in Cell Biology (58 citations), Molecular Biology (198 citations), Immunology and Allergy (10 citations), Cellular and Molecular Neuroscience (16 citations) and Materials Chemistry (40 citations). Lan Huang has collaborated with scholars based in China and United States. Frequent co-authors include Greg S. Martin, Franz Hofer, Xiaowei Wang, Xue Wang, Tian Bai, Xin Wang, Zhe Wang, Zhihong Qian, Hongsheng Chen and Chunguang Zhou. Their work appears in journals such as IEEE Access, Applied Mechanics and Materials, International Journal of Pattern Recognition and Artificial Intelligence and Nature Structural Biology.

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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