Shin‐Yu Lin

2.2k citations
104 papers · 1.7k · h-index 22

Impact in

Papers in

Shin‐Yu Lin

100 papers receiving 1.7k citations

Peers

Shin‐Yu Lin
Comparison fields: 5 of 131
  • Obstetrics and Gynecology 355
  • Pediatrics, Perinatology and Child Health 439
  • Toxicology 52
  • Sensory Systems 47
  • Endocrinology, Diabetes and Metabolism 139
Replace Charles Fournier with:
Charles Fournier France
Curt W. Burger Netherlands
Kenneth A. Pass United States
Koji Yoshimura Japan
Edward J. Pavlik United States
Laila Dahmoush United States
Moon Young Kim South Korea
Widukind Lenz Germany
Matti Nuutinen Finland
Jacques Lansac France
Shin‐Yu Lin relative to Charles Fournier France Charles Fournier's profile →
Citations per field
00.5×2×4×6×8×9.1×
Charles Fournier · 1×
Citations per year

Countries citing papers authored by Shin‐Yu Lin

Since Specialization
Citations

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

Fields of papers citing papers by Shin‐Yu Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shin‐Yu Lin. 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 Shin‐Yu Lin. The network helps show where Shin‐Yu Lin may publish in the future.

Co-authors

The 25 scholars most cited alongside Shin‐Yu Lin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Shin‐Yu Lin Line = papers co-authored together Shin‐Yu Lin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 104 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009188
2 201095
3 200293
4 200692
5 201177
6 201959
7 201952
8 201749
9 201141
10 201639
11 200837
12 201933
13 201832
14 201130
15 201230
16 200929
17 201125
18 201725
19 201825
20 200624

About Shin‐Yu Lin

Shin‐Yu Lin is a scholar working on Obstetrics and Gynecology, Pediatrics, Perinatology and Child Health, Genetics, Epidemiology and Cardiology and Cardiovascular Medicine, having authored 104 papers that have together received 1.7k indexed citations. Recurring topics across this work include Prenatal Screening and Diagnostics (14 papers), Gestational Diabetes Research and Management (11 papers), Genomic variations and chromosomal abnormalities (10 papers), Genetic Syndromes and Imprinting (7 papers), Pregnancy and preeclampsia studies (5 papers), Maternal and fetal healthcare (5 papers), Epigenetics and DNA Methylation (5 papers) and Maternal and Perinatal Health Interventions (5 papers). The work is most often cited by research in Obstetrics and Gynecology (355 citations), Pediatrics, Perinatology and Child Health (439 citations), Toxicology (52 citations), Sensory Systems (47 citations) and Endocrinology, Diabetes and Metabolism (139 citations). Shin‐Yu Lin has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Chien‐Nan Lee, Jin‐Chung Shih, Hung‐Yuan Li, Yi‐Ning Su, Ming‐Kwang Shyu, Jose Miguel Palacios-Jaraquemada, Yun Su, Chia‐Hua Lin, R. J. Dwayne Miller and Kevin J. Kubarych. Their work appears in journals such as PLoS ONE, Frontiers in Genetics, Diabetes Research and Clinical Practice, Ultrasound in Obstetrics and Gynecology and International Journal of Gynecology & Obstetrics.

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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