Wanmin Song

3.3k total citations · 1 hit paper
7 papers, 1.5k citations indexed

About

Wanmin Song is a scholar working on Molecular Biology, Infectious Diseases and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Wanmin Song has authored 7 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 2 papers in Infectious Diseases and 2 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Wanmin Song's work include Bacteriophages and microbial interactions (2 papers), Viral Infections and Vectors (2 papers) and Advanced biosensing and bioanalysis techniques (2 papers). Wanmin Song is often cited by papers focused on Bacteriophages and microbial interactions (2 papers), Viral Infections and Vectors (2 papers) and Advanced biosensing and bioanalysis techniques (2 papers). Wanmin Song collaborates with scholars based in United States. Wanmin Song's co-authors include Roger S. Lasken, Mark D. Driscoll, Xiaohong Wu, Jing Du, Zhenyu Sun, Seiyu Hosono, Michael D. Miller, Yuefen Du, A. Fawad Faruqi and Stephen F. Kingsmore and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Applied and Environmental Microbiology and Developmental Biology.

In The Last Decade

Wanmin Song

7 papers receiving 1.5k citations

Hit Papers

align trajectories

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.

Comprehensive human genome amplification using multiple displacement amplification

2002 1.1k citations Frank B. Dean, Seiyu Hosono et al. Proceedings of the National Academy of Sciences profile →

Peers

Wanmin Song

MB

GENET

ECOLO

CR

BE

John H. Leamon United States

Cameron N. Gundry United States

Robert Palais United States

Joshua G Vandersteen United States

Yuefen Du United States

A. Fawad Faruqi United States

Martin Kristian Raida Germany

Seiyu Hosono United States

Theresa L. Giesler United States

Maria Erali United States

John H. Leamon United States

Wanmin Song

819 ×0.8

MB

294 ×0.8

GENET

296 ×0.8

ECOLO

227 ×0.9

CR

398 ×2.2

BE

Citations per year, relative to Wanmin Song Wanmin Song (= 1×) peers John H. Leamon

Countries citing papers authored by Wanmin Song

Since Specialization

Citations

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

Fields of papers citing papers by Wanmin Song

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wanmin Song

This figure shows the co-authorship network connecting the top 25 collaborators of Wanmin Song. A scholar is included among the top collaborators of Wanmin Song 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 Wanmin Song. Wanmin Song is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Raghunathan, Arumugham, et al.. (2005). Genomic DNA Amplification from a Single Bacterium. Applied and Environmental Microbiology. 71(6). 3342–3347. 233 indexed citations

2.

Alsmadi, Osama, Wanmin Song, Michele Wisniewski, et al.. (2003). High accuracy genotyping directly from genomic DNA using a rolling circle amplification based assay. BMC Genomics. 4(1). 21–21. 43 indexed citations

3.

Dean, Frank B., Seiyu Hosono, Xiaohong Wu, et al.. (2002). Comprehensive human genome amplification using multiple displacement amplification. Proceedings of the National Academy of Sciences. 99(8). 5261–5266. 1092 indexed citations breakdown →

4.

Song, Wanmin, et al.. (2000). Degradation of Type IV Collagen by Matrix Metalloproteinases Is an Important Step in the Epithelial-Mesenchymal Transformation of the Endocardial Cushions. Developmental Biology. 227(2). 606–617. 76 indexed citations

5.

Song, Wanmin, Susan M. Majka, & Paul G. McGuire. (1999). Hepatocyte growth factor expression in the developing myocardium: Evidence for a role in the regulation of the mesenchymal cell phenotype and urokinase expression. Developmental Dynamics. 214(1). 92–100. 1 indexed citations

6.

Hjelle, Brian, Bruce M. Anderson, Norah Torrez‐Martinez, et al.. (1995). Prevalence and Geographic Genetic Variation of Hantaviruses of New World Harvest Mice (Reithrodontomys): Identification of a Divergent Genotype from a Costa Rican Reithrodontomys mexicanus. Virology. 207(2). 452–459. 64 indexed citations

7.

Torrez‐Martinez, Norah, Wanmin Song, & Brian Hjelle. (1995). Nucleotide Sequence Analysis of the M Genomic Segment of El Moro Canyon Hantavirus: Antigenic Distinction from Four Corners Hantavirus. Virology. 211(1). 336–338. 21 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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