Tin Louie

7.2k total citations
11 papers, 417 citations indexed

About

Tin Louie is a scholar working on Genetics, Pulmonary and Respiratory Medicine and Hematology. According to data from OpenAlex, Tin Louie has authored 11 papers receiving a total of 417 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Genetics, 4 papers in Pulmonary and Respiratory Medicine and 4 papers in Hematology. Recurrent topics in Tin Louie's work include Hemoglobinopathies and Related Disorders (4 papers), Iron Metabolism and Disorders (4 papers) and Cystic Fibrosis Research Advances (3 papers). Tin Louie is often cited by papers focused on Hemoglobinopathies and Related Disorders (4 papers), Iron Metabolism and Disorders (4 papers) and Cystic Fibrosis Research Advances (3 papers). Tin Louie collaborates with scholars based in United States, Australia and Canada. Tin Louie's co-authors include Mary J. Emond, Deborah A. Nickerson, Rasika A. Mathias, Kathleen C. Barnes, Julia Emerson, Ronald L. Gibson, Mark J. Rieder, Holly K. Tabor, Michael R. Knowles and Jason A. Dominitz and has published in prestigious journals such as Nature Genetics, Blood and Hepatology.

In The Last Decade

Tin Louie

10 papers receiving 413 citations

Peers

Tin Louie
John H. Gilliam United States
Nigel R. Swanson Australia
Roberto Mangoo‐Karim United States
Junya Fujimura Japan
Yuji Nishio Japan
Ella M. van den Berg‐Loonen Netherlands
Maria Luz Lara-Marquez United States
Balow Je United States
Matthias B. Moor Switzerland
Xue He China
John H. Gilliam United States
Tin Louie
Citations per year, relative to Tin Louie Tin Louie (= 1×) peers John H. Gilliam

Countries citing papers authored by Tin Louie

Since Specialization
Citations

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

Fields of papers citing papers by Tin Louie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tin Louie

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

All Works

11 of 11 papers shown
1.
Song, Yanwei, Takeshi Nishiyama, Tin Louie, et al.. (2023). Multi-ancestry genome-wide analysis identifies shared genetic effects and common genetic variants for self-reported sleep duration. Human Molecular Genetics. 32(18). 2797–2807. 5 indexed citations
2.
Agrawal, Pankaj B., Ruobing Wang, Hongmei Lisa Li, et al.. (2017). The Epithelial Sodium Channel Is a Modifier of the Long-Term Nonprogressive Phenotype Associated with F508del CFTR Mutations. American Journal of Respiratory Cell and Molecular Biology. 57(6). 711–720. 32 indexed citations
3.
4.
Qi, Qibin, Stephanie M. Gogarten, Leslie S. Emery, et al.. (2016). Genetic variation near IRS1 is associated with adiposity and a favorable metabolic profile in U.S.Hispanics/Latinos. Obesity. 24(11). 2407–2413. 6 indexed citations
5.
Gao, Li, Mary J. Emond, Tin Louie, et al.. (2015). Identification of Rare Variants in ATP8B4 as a Risk Factor for Systemic Sclerosis by Whole‐Exome Sequencing. Arthritis & Rheumatology. 68(1). 191–200. 33 indexed citations
6.
Emond, Mary J., Tin Louie, Julia Emerson, et al.. (2015). Exome Sequencing of Phenotypic Extremes Identifies CAV2 and TMC6 as Interacting Modifiers of Chronic Pseudomonas aeruginosa Infection in Cystic Fibrosis. PLoS Genetics. 11(6). e1005273–e1005273. 33 indexed citations
7.
McLaren, Christine E., Mary J. Emond, V. Nathan Subramaniam, et al.. (2015). Exome sequencing in HFE C282Y homozygous men with extreme phenotypes identifies a GNPAT variant associated with severe iron overload. Hepatology. 62(2). 429–439. 55 indexed citations
8.
McLaren, Gordon D., Mary J. Emond, V. Nathan Subramaniam, et al.. (2014). Exome Sequencing Identifies a GNPAT Variant Associated with Severe Iron Overload in HFE C282Y Homozygous Men with Extreme Phenotypes; Possible Role in Regulation of Hepcidin Expression. Blood. 124(21). 745–745. 1 indexed citations
9.
McLaren, Christine E., Mary J. Emond, Pradyumna D. Phatak, et al.. (2013). Exome Sequencing Identifies Genes and Variant Alleles Associated With Severity Of Iron Overload In Hemochromatosis HFE C282Y Homozygotes. Blood. 122(21). 179–179.
10.
Emond, Mary J., Tin Louie, Julia Emerson, et al.. (2012). Exome sequencing of extreme phenotypes identifies DCTN4 as a modifier of chronic Pseudomonas aeruginosa infection in cystic fibrosis. Nature Genetics. 44(8). 886–889. 155 indexed citations
11.
Dalrymple, Lorien S., Thomas D. Koepsell, Joshua N. Sampson, et al.. (2007). Hepatitis C Virus Infection and the Prevalence of Renal Insufficiency. Clinical Journal of the American Society of Nephrology. 2(4). 715–721. 77 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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