Yang Ni

3.2k total citations · 1 hit paper
74 papers, 1.4k citations indexed

About

Yang Ni is a scholar working on Molecular Biology, Artificial Intelligence and Accounting. According to data from OpenAlex, Yang Ni has authored 74 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 19 papers in Artificial Intelligence and 16 papers in Accounting. Recurrent topics in Yang Ni's work include Corporate Finance and Governance (15 papers), Gene expression and cancer classification (13 papers) and Financial Markets and Investment Strategies (13 papers). Yang Ni is often cited by papers focused on Corporate Finance and Governance (15 papers), Gene expression and cancer classification (13 papers) and Financial Markets and Investment Strategies (13 papers). Yang Ni collaborates with scholars based in United States, China and Canada. Yang Ni's co-authors include Tian Ge, Chia‐Yen Chen, Jordan W. Smoller, Yen‐Chen Anne Feng, Jeffrey Pittman, Samir Saadi, Omrane Guedhami, Sadok El Ghoul, Veerabhadran Baladandayuthapani and Francesco C. Stingo and has published in prestigious journals such as Nature Communications, Journal of the American Statistical Association and Bioinformatics.

In The Last Decade

Yang Ni

60 papers receiving 1.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Polygenic prediction via Bayesian regression and continuous shrinkage priors

2019 823 citations Yang Ni et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yang Ni United States	13	510	257	255	120	114	74	1.4k
José M. Pavía Spain	17	54 0.1×	38 0.1×	143 0.6×	63 0.5×	92 0.8×	143	1.2k
Erika Graf Germany	21	124 0.2×	9 0.0×	166 0.7×	168 1.4×	352 3.1×	72	1.8k
Hyunseung Kang United States	12	597 1.2×	8 0.0×	381 1.5×	40 0.3×	232 2.0×	36	1.6k
Stefano Young United States	8	98 0.2×	17 0.1×	180 0.7×	93 0.8×	140 1.2×	20	939
David Saunders United States	26	176 0.3×	14 0.1×	210 0.8×	28 0.2×	90 0.8×	113	2.5k
M Mezzetti Italy	24	154 0.3×	11 0.0×	658 2.6×	58 0.5×	73 0.6×	91	2.3k
Carl Johan Sundberg Sweden	46	816 1.6×	11 0.0×	1.7k 6.8×	30 0.3×	19 0.2×	180	6.1k
A. R. Jonckheere United Kingdom	7	67 0.1×	17 0.1×	130 0.5×	94 0.8×	399 3.5×	11	1.6k
Shun‐Chiao Chang United States	23	150 0.3×	18 0.1×	222 0.9×	7 0.1×	11 0.1×	51	1.7k

Countries citing papers authored by Yang Ni

Since Specialization

Citations

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

Fields of papers citing papers by Yang Ni

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yang Ni

This figure shows the co-authorship network connecting the top 25 collaborators of Yang Ni. A scholar is included among the top collaborators of Yang Ni 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 Yang Ni. Yang Ni 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

Chen, Liying, et al.. (2025). A probabilistic modeling framework for genomic networks incorporating sample heterogeneity. Cell Reports Methods. 5(2). 100984–100984. 1 indexed citations

Ni, Yang, et al.. (2025). Robust Bayesian graphical regression models for assessing tumor heterogeneity in proteomic networks. Biometrics. 81(1).

Ni, Yang, Chen Su, & Zeya Wang. (2025). Causal Structural Modeling of Survey Questionnaires via a Bootstrapped Ordinal Bayesian Network Approach. Psychometrika. 90(1). 229–250. 1 indexed citations

Ni, Yang, et al.. (2025). MR.RGM: an R package for fitting Bayesian multivariate bidirectional Mendelian randomization networks. Bioinformatics. 41(4). 1 indexed citations

Ni, Yang, et al.. (2025). The number of dissociation sets in connected graphs. Discrete Applied Mathematics. 373. 196–203.

He, Kejun, et al.. (2023). Functional Bayesian Networks for Discovering Causality from Multivariate Functional Data. Biometrics. 79(4). 3279–3293. 2 indexed citations

He, Kejun, et al.. (2023). Bayesian Nonlinear Tensor Regression with Functional Fused Elastic Net Prior. Technometrics. 65(4). 524–536. 1 indexed citations

Ni, Yang. (2023). Handbook of Bayesian Variable Selection. Journal of the American Statistical Association. 118(542). 1449–1450.

Das, Priyam, Christine B. Peterson, Yang Ni, et al.. (2022). Bayesian Hierarchical Quantile Regression with Application to Characterizing the Immune Architecture of Lung Cancer. Biometrics. 79(3). 2474–2488.

10.

Gaynanova, Irina, et al.. (2022). Phylogenetically informed Bayesian truncated copula graphical models for microbial association networks. The Annals of Applied Statistics. 16(4). 3 indexed citations

11.

Wang, Suping, Ruijie Chang, Shuxian Zhang, et al.. (2022). Social exclusion, thwarted belongingness, and perceived burdensomeness: construct validity and psychometric properties of the Interpersonal Needs Questionnaire among patients with sexually transmitted infections in Shanghai, China. BMC Psychology. 10(1). 29–29. 5 indexed citations

12.

Wang, Zeya, Yang Ni, Baoyu Jing, et al.. (2021). DNB: A Joint Learning Framework for Deep Bayesian Nonparametric Clustering. IEEE Transactions on Neural Networks and Learning Systems. 33(12). 7610–7620. 14 indexed citations

13.

Ni, Yang, Veerabhadran Baladandayuthapani, Marina Vannucci, & Francesco C. Stingo. (2021). Bayesian graphical models for modern biological applications. Statistical Methods & Applications. 31(2). 197–225. 16 indexed citations

14.

Ni, Yang, et al.. (2021). The role of sexual compulsivity in unprotected intercourse among STI patients in Shanghai, China. BMC Public Health. 21(1). 141–141. 8 indexed citations

15.

Shi, Yuan, Xiaoyue Yu, Ruijie Chang, et al.. (2021). The syndemic condition of psychosocial problems related to depression among sexually transmitted infections patients. PeerJ. 9. e12022–e12022. 5 indexed citations

16.

Chapkin, Robert S., et al.. (2020). Bayesian Causal Structural Learning with Zero-Inflated Poisson Bayesian Networks. Neural Information Processing Systems. 33. 5887–5897. 5 indexed citations

17.

Ni, Yang, Yuan Ji, & Peter Müller. (2020). Consensus Monte Carlo for Random Subsets Using Shared Anchors. Journal of Computational and Graphical Statistics. 29(4). 703–714. 8 indexed citations

18.

Wang, Suping, et al.. (2020). Psychosocial Syndemic of suicidal ideation: a cross-sectional study among sexually transmitted infection patients in Shanghai, China. BMC Public Health. 20(1). 1314–1314. 7 indexed citations

19.

Shpak, Max, Yang Ni, Jie Lü, & Peter Müller. (2017). Variance in estimated pairwise genetic distance under high versus low coverage sequencing: The contribution of linkage disequilibrium. Theoretical Population Biology. 117. 51–63. 4 indexed citations

20.

Ghoul, Sadok El, Omrane Guedhami, Yang Ni, Jeffrey Pittman, & Samir Saadi. (2012). Does Religion Matter to Equity Pricing. SSRN Electronic Journal. 2 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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