Tae Young Yang

766 total citations
28 papers, 468 citations indexed

About

Tae Young Yang is a scholar working on Statistics and Probability, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Tae Young Yang has authored 28 papers receiving a total of 468 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Statistics and Probability, 7 papers in Molecular Biology and 6 papers in Artificial Intelligence. Recurrent topics in Tae Young Yang's work include Gene expression and cancer classification (7 papers), Software Reliability and Analysis Research (6 papers) and Bayesian Methods and Mixture Models (6 papers). Tae Young Yang is often cited by papers focused on Gene expression and cancer classification (7 papers), Software Reliability and Analysis Research (6 papers) and Bayesian Methods and Mixture Models (6 papers). Tae Young Yang collaborates with scholars based in South Korea, United States and Canada. Tae Young Yang's co-authors include Lynn Kuo, Tim B. Swartz, Albert Vexler, Yoel Haitovsky, Dong‐Min Kim, Na Ra Yun, So Yeon Ryu, Chang Youl Lee, Sung Heui Shin and Jong Soo Choi and has published in prestigious journals such as Journal of the American Statistical Association, PLoS ONE and Statistics in Medicine.

In The Last Decade

Tae Young Yang

27 papers receiving 439 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tae Young Yang South Korea	11	221	159	157	65	61	28	468
Catherine Huber‐Carol France	5	215 1.0×	23 0.1×	96 0.6×	37 0.6×	117 1.9×	6	354
Tsai‐Hung Fan Taiwan	14	346 1.6×	24 0.2×	153 1.0×	80 1.2×	188 3.1×	44	458
Benjamin Epstein United States	7	289 1.3×	41 0.3×	167 1.1×	36 0.6×	185 3.0×	10	478
Naif Alotaibi Saudi Arabia	14	309 1.4×	9 0.1×	43 0.3×	47 0.7×	178 2.9×	47	449
M. B. Rajarshi India	10	268 1.2×	14 0.1×	60 0.4×	77 1.2×	124 2.0×	31	392
J. Miguel Marín Spain	11	186 0.8×	12 0.1×	13 0.1×	101 1.6×	31 0.5×	27	410
Isha Dewan India	13	249 1.1×	26 0.2×	123 0.8×	76 1.2×	107 1.8×	60	400
Mohd. Arshad India	11	176 0.8×	12 0.1×	58 0.4×	54 0.8×	93 1.5×	43	319
Fredrik Törner Sweden	8	6 0.0×	99 0.6×	55 0.4×	27 0.4×	8 0.1×	18	185
B.W.M. Bettonvil Netherlands	9	24 0.1×	46 0.3×	9 0.1×	17 0.3×	70 1.1×	18	361

Countries citing papers authored by Tae Young Yang

Since Specialization

Citations

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

Fields of papers citing papers by Tae Young Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tae Young Yang. 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 Tae Young Yang. The network helps show where Tae Young Yang may publish in the future.

Co-authorship network of co-authors of Tae Young Yang

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

All Works

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20 of 20 papers shown

Jeong, Hye Yun, Hyun‐Ju An, Min Ji Sung, et al.. (2023). Proteomic profiling of protein expression changes after 3 months-exercise in ESRD patients on hemodialysis. BMC Nephrology. 24(1). 102–102.

Yang, Tae Young & Seongmun Jeong. (2017). Controlling the false-discovery rate by procedures adapted to the length bias of RNA-Seq. Journal of the Korean Statistical Society. 47(1). 13–23. 2 indexed citations

Yang, Tae Young, Eun Young Jang, Yeonhee Ryu, et al.. (2017). Effect of acupuncture on Lipopolysaccharide-induced anxiety-like behavioral changes: involvement of serotonin system in dorsal Raphe nucleus. BMC Complementary and Alternative Medicine. 17(1). 528–528. 17 indexed citations

Shim, Minjung, Tae Young Yang, Eunju Kim, et al.. (2016). Hepatic Infarction Caused by Portal Vein Thrombophlebitis Misdiagnosed as Infiltrative Hepatic Malignancy with Neoplastic Thrombus. Korean Journal of Gastroenterology. 68(3). 156–156. 2 indexed citations

Yang, Tae Young. (2012). Simple binary segmentation frameworks for identifying variation in DNA copy number. BMC Bioinformatics. 13(1). 277–277. 2 indexed citations

Yang, Tae Young. (2011). A SATS algorithm for jointly identifying multiple differentially expressed gene sets. Statistics in Medicine. 30(16). 2028–2039. 2 indexed citations

Kim, Dong‐Min, Na Ra Yun, Ganesh Prasad Neupane, et al.. (2011). Differences in Clinical Features According to Boryoung and Karp Genotypes of Orientia tsutsugamushi. PLoS ONE. 6(8). e22731–e22731. 46 indexed citations

Yang, Tae Young. (2008). Efficient multi-class cancer diagnosis algorithm, using a global similarity pattern. Computational Statistics & Data Analysis. 53(3). 756–765. 8 indexed citations

Yang, Tae Young & Tim B. Swartz. (2005). Applications of Binary Segmentation to the Estimation of Quantal Response Curves and Spatial Intensity. Biometrical Journal. 47(4). 489–501. 1 indexed citations

10.

Yang, Tae Young. (2005). A tree-based model for homogeneous groupings of multinomials. Statistics in Medicine. 24(22). 3513–3522. 5 indexed citations

11.

Swartz, Tim B., Yoel Haitovsky, Albert Vexler, & Tae Young Yang. (2004). Bayesian identifiability and misclassification in multinomial data. Canadian Journal of Statistics. 32(3). 285–302. 36 indexed citations

12.

Kuo, Lynn & Tae Young Yang. (2004). An improved collapsed Gibbs sampler for Dirichlet process mixing models. Computational Statistics & Data Analysis. 50(3). 659–674. 3 indexed citations

13.

Kim, Dong Jun, Tae Young Yang, Eun Young Oh, et al.. (2001). Insulin Secretion and Insulin Sensitivity in Korean Subjects with Impaired Glucose Intolerance.. Korean Diabetes Journal. 24(3). 356–364. 3 indexed citations

14.

Yang, Tae Young & Lynn Kuo. (2001). Bayesian Binary Segmentation Procedure for a Poisson Process With Multiple Changepoints. Journal of Computational and Graphical Statistics. 10(4). 772–785. 45 indexed citations

15.

Yang, Tae Young & Lynn Kuo. (1999). Bayesian computation for the superposition of nonhomogeneous poisson processes. Canadian Journal of Statistics. 27(3). 547–556. 12 indexed citations

16.

Kuo, Lynn, et al.. (1997). Bayes inference for S-shaped software-reliability growth models. IEEE Transactions on Reliability. 46(1). 76–80, 87. 20 indexed citations

17.

Kuo, Lynn & Tae Young Yang. (1996). Bayesian Computation for Nonhomogeneous Poisson Processes in Software Reliability. Journal of the American Statistical Association. 91(434). 763–773. 114 indexed citations

18.

Kuo, Lynn & Tae Young Yang. (1995). Bayesian Computation of Software Reliability. Journal of Computational and Graphical Statistics. 4(1). 65–82. 32 indexed citations

19.

Kuo, Lynn & Tae Young Yang. (1995). Bayesian Computation of Software Reliability. Journal of Computational and Graphical Statistics. 4(1). 65–65. 15 indexed citations

20.

Yang, Tae Young. (1994). Computational approaches to Bayesian inference for software reliability. OpenCommons - UConn (University of Connecticut). 5 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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