Ching‐Ti Liu

77.8k total citations · 1 hit paper
181 papers, 5.8k citations indexed

About

Ching‐Ti Liu is a scholar working on Genetics, Molecular Biology and Physiology. According to data from OpenAlex, Ching‐Ti Liu has authored 181 papers receiving a total of 5.8k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Genetics, 54 papers in Molecular Biology and 23 papers in Physiology. Recurrent topics in Ching‐Ti Liu's work include Genetic Associations and Epidemiology (46 papers), Epigenetics and DNA Methylation (17 papers) and Genetic Mapping and Diversity in Plants and Animals (16 papers). Ching‐Ti Liu is often cited by papers focused on Genetic Associations and Epidemiology (46 papers), Epigenetics and DNA Methylation (17 papers) and Genetic Mapping and Diversity in Plants and Animals (16 papers). Ching‐Ti Liu collaborates with scholars based in United States, Taiwan and China. Ching‐Ti Liu's co-authors include Morgan E. Levine, Kurt Lohman, Lifang Hou, Alex P. Reiner, Yun Li, Abraham Aviv, Andrea Baccarelli, Austin Quach, Stefania Bandinelli and Luigi Ferrucci and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Circulation.

In The Last Decade

Ching‐Ti Liu

171 papers receiving 5.7k citations

Hit Papers

An epigenetic biomarker of aging for lifespan and healthspan 2018 2026 2020 2023 2018 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ching‐Ti Liu United States 34 2.4k 1.0k 966 750 492 181 5.8k
Aiyi Liu United States 40 1.5k 0.6× 640 0.6× 820 0.8× 565 0.8× 484 1.0× 232 6.0k
Themistocles L. Assimes United States 37 3.4k 1.4× 1.4k 1.4× 1.2k 1.2× 1.2k 1.5× 533 1.1× 121 7.4k
Dawn L. DeMeo United States 51 2.6k 1.1× 1.0k 1.0× 2.2k 2.2× 581 0.8× 533 1.1× 203 8.7k
Shelley A. Cole United States 42 2.0k 0.8× 1.6k 1.6× 1.3k 1.4× 488 0.7× 903 1.8× 281 6.6k
David V. Conti United States 42 2.2k 0.9× 1.8k 1.8× 1.2k 1.2× 380 0.5× 445 0.9× 228 6.5k
Jessica Lasky‐Su United States 44 1.8k 0.7× 944 0.9× 2.0k 2.0× 346 0.5× 466 0.9× 245 6.2k
Liming Liang United States 47 3.5k 1.4× 2.0k 2.0× 1.7k 1.7× 598 0.8× 834 1.7× 269 8.2k
Jacob Hjelmborg Denmark 46 1.5k 0.6× 1.4k 1.3× 1.9k 1.9× 1.1k 1.5× 494 1.0× 191 7.4k
Martin A. Kennedy New Zealand 41 2.3k 0.9× 1.0k 1.0× 515 0.5× 502 0.7× 434 0.9× 219 6.8k
Sarah J. Lewis United Kingdom 44 1.1k 0.5× 1.3k 1.3× 1.0k 1.1× 929 1.2× 534 1.1× 184 6.4k

Countries citing papers authored by Ching‐Ti Liu

Since Specialization
Citations

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

Fields of papers citing papers by Ching‐Ti Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ching‐Ti Liu. 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 Ching‐Ti Liu. The network helps show where Ching‐Ti Liu may publish in the future.

Co-authorship network of co-authors of Ching‐Ti Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Ching‐Ti Liu. A scholar is included among the top collaborators of Ching‐Ti Liu 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 Ching‐Ti Liu. Ching‐Ti Liu 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
1.
Jaeger, Byron C., Haiying Chen, Marc D. Rudolph, et al.. (2024). Subclinical Vascular Disorders in Relation to Cognitive Decline and Impairment: The Multi‐Ethnic Study of Atherosclerosis. Alzheimer s & Dementia. 20(S7).
2.
Liu, Ching‐Ti, et al.. (2024). A Statistical Method for Protocol Modifications With Heterogeneous Population Variances. Statistics in Biopharmaceutical Research. 17(2). 260–265. 1 indexed citations
3.
Wu, Peitao, Josée Dupuis, & Ching‐Ti Liu. (2023). Identifying important gene signatures of BMI using network structure‐aided nonparametric quantile regression. Statistics in Medicine. 42(10). 1625–1639. 2 indexed citations
4.
Laroche, Fabrice, Sheng Li, Ning Shen, et al.. (2023). S1P1 Threonine 236 Phosphorylation Mediates the Invasiveness of Triple-Negative Breast Cancer and Sensitivity to FTY720. Cells. 12(7). 980–980. 6 indexed citations
5.
Lee, Yen‐Han, Trishnee Bhurosy, Yen‐Chang Chang, Ching‐Ti Liu, & Mack Shelley. (2022). Associations of alcohol consumption and dietary behaviors with severe cognitive impairment among Chinese older men and women. Journal of Substance Use. 28(2). 235–242. 3 indexed citations
6.
Lange, Leslie A., François Aguet, Kristin Ardlie, et al.. (2022). Gene expression associations with body mass index in the Multi-Ethnic Study of Atherosclerosis. International Journal of Obesity. 47(2). 109–116. 5 indexed citations
8.
Schmitz, Lauren, Wei Zhao, Scott M. Ratliff, et al.. (2021). The Socioeconomic Gradient in Epigenetic Ageing Clocks: Evidence from the Multi-Ethnic Study of Atherosclerosis and the Health and Retirement Study. Epigenetics. 17(6). 589–611. 74 indexed citations
9.
Lent, Samantha, Andrés Cárdenas, Sheryl L. Rifas‐Shiman, et al.. (2021). Detecting Differentially Methylated Regions with Multiple Distinct Associations. Epigenomics. 13(6). 451–464. 16 indexed citations
10.
Shen, Ning, Theodoros Karantanos, Dun Li, et al.. (2021). DLST-dependence dictates metabolic heterogeneity in TCA-cycle usage among triple-negative breast cancer. Communications Biology. 4(1). 1289–1289. 39 indexed citations
11.
Xu, Hanfei, Karen Schwander, Michael R. Brown, et al.. (2021). Lifestyle Risk Score: handling missingness of individual lifestyle components in meta-analysis of gene-by-lifestyle interactions. European Journal of Human Genetics. 29(5). 839–850. 3 indexed citations
12.
Lee, Yen‐Han, et al.. (2021). Association between medical marijuana legalization and sources of obtaining marijuana among adults in the United States. Journal of Substance Use. 27(1). 27–33. 1 indexed citations
14.
Zhou, Xiang, Min Zhang, Wei Zhao, et al.. (2019). Bayesian shrinkage estimation of high dimensional causal mediation effects in omics studies. Biometrics. 76(3). 700–710. 45 indexed citations
15.
Geovanini, Glaucylara Reis, Rui Wang, Jia Weng, et al.. (2018). Elevations in neutrophils with obstructive sleep apnea: The Multi-Ethnic Study of Atherosclerosis (MESA). International Journal of Cardiology. 257. 318–323. 23 indexed citations
16.
Baranski, Thomas, Aldi T. Kraja, Jill L. Fink, et al.. (2018). A high throughput, functional screen of human Body Mass Index GWAS loci using tissue-specific RNAi Drosophila melanogaster crosses. PLoS Genetics. 14(4). e1007222–e1007222. 23 indexed citations
17.
Liu, Ching‐Ti, et al.. (2018). UFD1 contributes to MYC-mediated leukemia aggressiveness through suppression of the proapoptotic unfolded protein response. Leukemia. 32(11). 2339–2351. 25 indexed citations
18.
Reardon, Brian, Ronald G. Crystal, Denise K. Houston, et al.. (2013). Vitamin D-responsive SGPP2 variants associated with lung cell expression and lung function. BMC Medical Genetics. 14(1). 122–122. 8 indexed citations
19.
Qi, Qibin, Claudia Menzaghi, Shelly G. Smith, et al.. (2012). Genome-wide association analysis identifies TYW3/CRYZ and NDST4 loci associated with circulating resistin levels. Human Molecular Genetics. 21(21). 4774–4780. 33 indexed citations
20.
Liu, Ching‐Ti, et al.. (2012). Functional analysis of HapMap SNPs. Gene. 511(2). 358–363. 6 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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