T. Y. Ling

6.7k total citations
2 papers, 4 citations indexed

About

T. Y. Ling is a scholar working on Molecular Biology, Geriatrics and Gerontology and Physiology. According to data from OpenAlex, T. Y. Ling has authored 2 papers receiving a total of 4 indexed citations (citations by other indexed papers that have themselves been cited), including 1 paper in Molecular Biology, 1 paper in Geriatrics and Gerontology and 1 paper in Physiology. Recurrent topics in T. Y. Ling's work include Balance, Gait, and Falls Prevention (1 paper), Frailty in Older Adults (1 paper) and Single-cell and spatial transcriptomics (1 paper). T. Y. Ling is often cited by papers focused on Balance, Gait, and Falls Prevention (1 paper), Frailty in Older Adults (1 paper) and Single-cell and spatial transcriptomics (1 paper). T. Y. Ling collaborates with scholars based in China. T. Y. Ling's co-authors include Qingfeng Chen, Yi Pan, Min Li, Ruiqing Zheng, Wei Lan, Jianwen Xu, Ling Wang and Zhao Wang and has published in prestigious journals such as PLoS Computational Biology and BMC Geriatrics.

In The Last Decade

T. Y. Ling

1 paper receiving 4 citations

Peers — A (Enhanced Table)

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

Name	h					Papers	Cites
T. Y. Ling China	1	4	1	1	1	2	4
Jon Arizti-Sanz United States	1	4 1.0×				2	4
David Scott United Kingdom	2	4 1.0×			1 1.0×	3	8
Alessandro De Falco Italy	2	4 1.0×				9	6
Han Xiang China	2	4 1.0×			1 1.0×	3	4
J. H. Zou China	2	4 1.0×				5	8
Mathias Gorski Germany	3	4 1.0×			1 1.0×	7	10
Demian Kong China	2	4 1.0×			1 1.0×	2	4
Kálmán Bódis Germany	2	4 1.0×				4	6
Jonah Cool United States	2	4 1.0×	1 1.0×			2	11
Aashis Thapa United States	2	4 1.0×				4	6

Countries citing papers authored by T. Y. Ling

Since Specialization

Citations

This map shows the geographic impact of T. Y. Ling'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 T. Y. Ling with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Y. Ling more than expected).

Fields of papers citing papers by T. Y. Ling

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by T. Y. Ling. 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 T. Y. Ling. The network helps show where T. Y. Ling may publish in the future.

Co-authorship network of co-authors of T. Y. Ling

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

All Works

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2 of 2 papers shown

1.

Ling, T. Y., et al.. (2025). A machine learning-based fall-risk score for severity of fall-related adverse outcomes in community older adults. BMC Geriatrics. 25(1). 724–724.

2.

Lan, Wei, T. Y. Ling, Qingfeng Chen, et al.. (2024). scMoMtF: An interpretable multitask learning framework for single-cell multi-omics data analysis. PLoS Computational Biology. 20(12). e1012679–e1012679. 4 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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