Loling Song

1.6k total citations · 1 hit paper
5 papers, 1.3k citations indexed

About

Loling Song is a scholar working on Molecular Biology, Biomedical Engineering and Cellular and Molecular Neuroscience. According to data from OpenAlex, Loling Song has authored 5 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Molecular Biology, 2 papers in Biomedical Engineering and 1 paper in Cellular and Molecular Neuroscience. Recurrent topics in Loling Song's work include 3D Printing in Biomedical Research (2 papers), Metabolism, Diabetes, and Cancer (2 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (1 paper). Loling Song is often cited by papers focused on 3D Printing in Biomedical Research (2 papers), Metabolism, Diabetes, and Cancer (2 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (1 paper). Loling Song collaborates with scholars based in United States and Germany. Loling Song's co-authors include Joan S. Brugge, Sizhen Gao, Zachary T. Schafer, Pere Puigserver, Zachary Gerhart‐Hines, Zhenyang Jiang, Hanna Y. Irie, Alexandra Grassian, Taru Muranen and Fabiana C. Morales and has published in prestigious journals such as Nature, Cancer Cell and Cancer Research.

In The Last Decade

Loling Song

5 papers receiving 1.3k 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.

Antioxidant and oncogene rescue of metabolic defects caused by loss of matrix attachment

2009 808 citations Zachary T. Schafer, Alexandra Grassian et al. Nature profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Loling Song United States	4	842	461	290	212	167	5	1.3k
Antonia Bellizzi Italy	20	1.2k 1.4×	424 0.9×	554 1.9×	289 1.4×	80 0.5×	24	1.7k
Melissa D. Landis United States	23	940 1.1×	393 0.9×	868 3.0×	146 0.7×	278 1.7×	28	1.8k
Mark Humphrey United States	9	835 1.0×	331 0.7×	606 2.1×	108 0.5×	139 0.8×	10	1.5k
Shuenn-Chen Yang Taiwan	18	994 1.2×	375 0.8×	474 1.6×	183 0.9×	82 0.5×	22	1.5k
Smitha Pillai United States	22	1.2k 1.4×	413 0.9×	469 1.6×	111 0.5×	91 0.5×	34	1.8k
Joseph Negri United States	21	933 1.1×	219 0.5×	613 2.1×	164 0.8×	154 0.9×	47	1.6k
Mitsuyo Ohmura Japan	13	810 1.0×	365 0.8×	295 1.0×	128 0.6×	51 0.3×	17	1.2k
Brian A. Joughin United States	23	1.2k 1.4×	251 0.5×	357 1.2×	267 1.3×	101 0.6×	40	1.7k
Doris R. Siwak United States	18	1.2k 1.4×	224 0.5×	462 1.6×	137 0.6×	71 0.4×	27	1.7k
Evgeny V. Denisov Russia	22	679 0.8×	494 1.1×	700 2.4×	236 1.1×	191 1.1×	92	1.6k

Countries citing papers authored by Loling Song

Since Specialization

Citations

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

Fields of papers citing papers by Loling Song

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Loling Song

This figure shows the co-authorship network connecting the top 25 collaborators of Loling Song. A scholar is included among the top collaborators of Loling 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 Loling Song. Loling 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:

5 of 5 papers shown

1.

Muranen, Taru, Laura M. Selfors, Devin Worster, et al.. (2012). Inhibition of PI3K/mTOR Leads to Adaptive Resistance in Matrix-Attached Cancer Cells. Cancer Cell. 21(2). 227–239. 315 indexed citations

2.

Muranen, Taru, Laura M. Selfors, Devin Worster, et al.. (2012). Abstract 4836: Inhibition of PI3K/mTOR leads to adaptive resistance in extracellular matrix attached cancer cells. Cancer Research. 72(8_Supplement). 4836–4836. 1 indexed citations

3.

Schafer, Zachary T., Alexandra Grassian, Loling Song, et al.. (2009). Antioxidant and oncogene rescue of metabolic defects caused by loss of matrix attachment. Nature. 461(7260). 109–113. 808 indexed citations breakdown →

4.

Song, Loling, Carsten Beta, Albert Bae, et al.. (2006). Dictyostelium discoideum chemotaxis: Threshold for directed motion. European Journal of Cell Biology. 85(9-10). 981–989. 156 indexed citations

5.

Song, Loling, et al.. (2004). Using Microfluidic Channel Networks to Generate Gradients for Studying Cell Migration. Humana Press eBooks. 294. 347–358. 13 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.

Explore authors with similar magnitude of impact