Pixu Shi

580 total citations
11 papers, 185 citations indexed

About

Pixu Shi is a scholar working on Molecular Biology, Oncology and Artificial Intelligence. According to data from OpenAlex, Pixu Shi has authored 11 papers receiving a total of 185 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Oncology and 3 papers in Artificial Intelligence. Recurrent topics in Pixu Shi's work include Metabolomics and Mass Spectrometry Studies (3 papers), Geochemistry and Geologic Mapping (3 papers) and Brain Metastases and Treatment (2 papers). Pixu Shi is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (3 papers), Geochemistry and Geologic Mapping (3 papers) and Brain Metastases and Treatment (2 papers). Pixu Shi collaborates with scholars based in United States, Australia and Sweden. Pixu Shi's co-authors include Hongzhe Li, Anru R. Zhang, Jiarui Lu, Mark E. Mikkelsen, Dylan S. Small, Kevin Huynh, Rima Kaddurah‐Daouk, Peter J. Meikle, Kaj Blennow and Pieter C. Dorrestein and has published in prestigious journals such as Journal of the American Statistical Association, Biometrics and Genome biology.

In The Last Decade

Pixu Shi

11 papers receiving 182 citations

Peers

Pixu Shi

MB

AI

SP

MM

PERIO

Irina Gaynanova United States

W. J. Zhu China

Aman Rana United States

Oscar Hernán Madrid Padilla United States

Arash Mehrjou Switzerland

Kazuo Yoshimoto Japan

Pedro Sanchez United Kingdom

Arup Gayen

Sachin Aryal United States

Ishan Manandhar United States

Irina Gaynanova United States

Pixu Shi

104 ×1.1

MB

24 ×0.3

AI

21 ×0.5

SP

0 ×0.0

MM

4 ×0.3

PERIO

Citations per year, relative to Pixu Shi Pixu Shi (= 1×) peers Irina Gaynanova

Countries citing papers authored by Pixu Shi

Since Specialization

Citations

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

Fields of papers citing papers by Pixu Shi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pixu Shi

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

All Works

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11 of 11 papers shown

1.

Kennedy, Lucy Boyce, Amanda E.D. Van Swearingen, Marissa R. Lee, et al.. (2025). A comprehensive, multi-center, immunogenomic analysis of melanoma brain metastases. Acta Neuropathologica Communications. 13(1). 123–123. 1 indexed citations

2.

Kim, Yeon Ji, et al.. (2025). Glucagon-Like Peptide 1 Receptor (Glp1r) Deficiency Does Not Appreciably Alter Airway Inflammation or Gut-Lung Microbiome Axis in a Mouse Model of Obese Allergic Airways Disease and Bariatric Surgery. Journal of Asthma and Allergy. Volume 18. 285–305. 1 indexed citations

3.

Swearingen, Amanda E.D. Van, Marissa R. Lee, Alexander B. Sibley, et al.. (2025). Genomic and immune profiling of breast cancer brain metastases. Acta Neuropathologica Communications. 13(1). 99–99. 1 indexed citations

4.

Batra, Richa, Bryan J. Neth, Cameron Martino, et al.. (2024). Serum and CSF metabolomics analysis shows Mediterranean Ketogenic Diet mitigates risk factors of Alzheimer’s disease. PubMed. 2(1). 15–15. 14 indexed citations

5.

Shi, Pixu, Cameron Martino, Stefan Janssen, et al.. (2024). TEMPTED: time-informed dimensionality reduction for longitudinal microbiome studies. Genome biology. 25(1). 317–317. 2 indexed citations

6.

Shi, Pixu, et al.. (2022). Guaranteed Functional Tensor Singular Value Decomposition. Journal of the American Statistical Association. 119(546). 995–1007. 8 indexed citations

7.

Shi, Pixu, et al.. (2021). High-dimensional log-error-in-variable regression with applications to microbial compositional data analysis. Biometrika. 109(2). 405–420. 10 indexed citations

8.

Lu, Jiarui, Pixu Shi, & Hongzhe Li. (2018). Generalized Linear Models With Linear Constraints for Microbiome Compositional Data. Biometrics. 75(1). 235–244. 42 indexed citations

9.

Shi, Pixu & Hongzhe Li. (2017). A Model for Paired-Multinomial Data and Its Application to Analysis of Data on a Taxonomic Tree. Biometrics. 73(4). 1266–1278. 10 indexed citations

10.

Shi, Pixu, et al.. (2016). Randomization Inference and Sensitivity Analysis for Composite Null Hypotheses With Binary Outcomes in Matched Observational Studies. Journal of the American Statistical Association. 112(517). 321–331. 15 indexed citations

11.

Shi, Pixu, Anru R. Zhang, & Hongzhe Li. (2016). Regression analysis for microbiome compositional data. The Annals of Applied Statistics. 10(2). 81 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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