Lin Gao

4.5k total citations · 1 hit paper
154 papers, 3.2k citations indexed

About

Lin Gao is a scholar working on Molecular Biology, Computational Theory and Mathematics and Statistical and Nonlinear Physics. According to data from OpenAlex, Lin Gao has authored 154 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 128 papers in Molecular Biology, 39 papers in Computational Theory and Mathematics and 20 papers in Statistical and Nonlinear Physics. Recurrent topics in Lin Gao's work include Bioinformatics and Genomic Networks (77 papers), Gene expression and cancer classification (38 papers) and Computational Drug Discovery Methods (37 papers). Lin Gao is often cited by papers focused on Bioinformatics and Genomic Networks (77 papers), Gene expression and cancer classification (38 papers) and Computational Drug Discovery Methods (37 papers). Lin Gao collaborates with scholars based in China, Canada and United States. Lin Gao's co-authors include Liang Yu, Xiaoke Ma, Bingbo Wang, Qiguang Miao, Jiachen Liu, Ying Cao, Xingli Guo, Xiaofei Yang, Yuxuan Hu and Peng Gang Sun and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Lin Gao

147 papers receiving 3.1k citations

Hit Papers

Advance and Prospects of AdaBoost Algorithm 2013 2026 2017 2021 2013 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Advance and Prospects of AdaBoost Algorithm
    2013 323 citations Lin Gao et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Lin Gao China 33 2.1k 623 499 418 389 154 3.2k
Mehmet Koyutürk United States 30 1.7k 0.8× 180 0.3× 412 0.8× 131 0.3× 307 0.8× 122 2.7k
Xiaoke Ma China 29 1.1k 0.5× 288 0.5× 167 0.3× 802 1.9× 774 2.0× 144 2.6k
Alfredo Ferro Italy 30 1.4k 0.7× 784 1.3× 350 0.7× 69 0.2× 395 1.0× 109 2.3k
Rosalba Giugno Italy 31 1.5k 0.7× 639 1.0× 305 0.6× 92 0.2× 508 1.3× 108 2.8k
Lun Hu China 29 1.4k 0.7× 197 0.3× 863 1.7× 210 0.5× 550 1.4× 105 2.4k
Xiujuan Lei China 31 2.3k 1.1× 1.2k 1.9× 766 1.5× 71 0.2× 558 1.4× 186 3.4k
Xiang‐Sun Zhang China 24 1.2k 0.6× 115 0.2× 330 0.7× 493 1.2× 311 0.8× 79 2.3k
Kil To Chong South Korea 38 2.2k 1.1× 279 0.4× 536 1.1× 85 0.2× 597 1.5× 355 5.7k
Maozu Guo China 29 2.1k 1.0× 925 1.5× 593 1.2× 75 0.2× 826 2.1× 214 3.7k
Ming Hao United States 26 2.4k 1.2× 621 1.0× 577 1.2× 127 0.3× 452 1.2× 126 5.1k

Countries citing papers authored by Lin Gao

Since Specialization
Citations

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

Fields of papers citing papers by Lin Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lin Gao

This figure shows the co-authorship network connecting the top 25 collaborators of Lin Gao. A scholar is included among the top collaborators of Lin Gao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lin Gao. Lin Gao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Li, Chunpeng, Weiwei Dai, Lingxiao Zhang, et al.. (2024). Two-stage deep neural network for diagnosing fungal keratitis via in vivo confocal microscopy images. Scientific Reports. 14(1). 18432–18432. 4 indexed citations
4.
Huang, Zhaoyang, et al.. (2024). Accurate RNA velocity estimation based on multibatch network reveals complex lineage in batch scRNA-seq data. BMC Biology. 22(1). 290–290. 13 indexed citations
5.
Wang, Lanying, Yuxuan Hu, & Lin Gao. (2024). Adjustment of scRNA-seq data to improve cell-type decomposition of spatial transcriptomics. Briefings in Bioinformatics. 25(2). 3 indexed citations
6.
Xiao, Wen, Han Li, Lang Peng, et al.. (2023). Deciphering driver regulators of cell fate decisions from single-cell transcriptomics data with CEFCON. Nature Communications. 14(1). 8459–8459. 7 indexed citations
7.
Gao, Lin, et al.. (2023). scHi-CSim: a flexible simulator that generates high-fidelity single-cell Hi-C data for benchmarking. Journal of Molecular Cell Biology. 15(1). 2 indexed citations
8.
Gao, Lin, et al.. (2023). GOLF-Net: Global and local association fusion network for COVID-19 lung infection segmentation. Computers in Biology and Medicine. 164. 107361–107361. 3 indexed citations
9.
Ao, Chunyan, et al.. (2020). Prediction of antioxidant proteins using hybrid feature representation method and random forest. Genomics. 112(6). 4666–4674. 55 indexed citations
10.
Gao, Lin, et al.. (2018). SF-Net: Learning scene flow from RGB-D images with CNNs. ORCA Online Research @Cardiff (Cardiff University). 281. 5 indexed citations
11.
Li, Feng, Lin Gao, Xiaoke Ma, & Xiaofei Yang. (2016). Detection of driver pathways using mutated gene network in cancer. Molecular BioSystems. 12(7). 2135–2141. 7 indexed citations
12.
Shi, Kai, Lin Gao, & Bingbo Wang. (2016). Discovering potential cancer driver genes by an integrated network-based approach. Molecular BioSystems. 12(9). 2921–2931. 29 indexed citations
13.
Gao, Lin, et al.. (2016). Uncovering Driver DNA Methylation Events in Nonsmoking Early Stage Lung Adenocarcinoma. BioMed Research International. 2016. 1–10. 5 indexed citations
14.
Gao, Lin, et al.. (2015). Identifying module biomarker in type 2 diabetes mellitus by discriminative area of functional activity. BMC Bioinformatics. 16(1). 92–92. 18 indexed citations
15.
Gao, Lin. (2012). Feature Selection of Biomedical Literature by Membrane ParticleSwarm Optimizer and Information Entropy. Xi'an Jiaotong Daxue xuebao. 1 indexed citations
16.
Gao, Lin. (2010). A Bio-Entity Recognition Algorithm for Literature by Conditional Random Field Model Based on Improved Particle Swarm Optimizer. Xi'an Jiaotong Daxue xuebao. 1 indexed citations
17.
Lin, Mao-Jen, et al.. (2008). Benzene-di-N-Substituted Carbamates as Conformationally Constrained Substrate Analogs of Cholesterol Esterase. The Protein Journal. 27(5). 276–282. 3 indexed citations
18.
Gao, Lin, et al.. (2006). Probing Structure–Function Relationships of Serine Hydrolases and Proteases with Carbamate and Thiocarbamate Inhibitors. The Protein Journal. 25(1). 33–43. 14 indexed citations
19.
Gao, Lin. (2004). DNA algorithm for minimum vertex cover problem based on molecular computation. Systems engineering and electronics. 1 indexed citations
20.
Gao, Lin. (2003). A DNA Algorithm for Graph Vertex Coloring Problem. Dianzi xuebao. 8 indexed citations

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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