World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
70
Citations
23689
World Ranking
273
National Ranking
151

Biology and Biochemistry

D-Index
93
Citations
42002
World Ranking
2066
National Ranking
1127

Research.com Recognitions

  • 2000 - Fellow of the American Statistical Association (ASA)

Overview

Xihong Lin is affiliated with Harvard University in the United States and has made significant contributions to the fields of Biochemistry, Genetics and Molecular Biology, and Medicine. Their research output spans a range of subfields, including Genetics, Molecular Biology, Statistics and Probability, Oncology, and Modeling and Simulation.

The scientist's main research topics cover Genetic Associations and Epidemiology, COVID-19 epidemiological studies, Epigenetics and DNA Methylation, Genomics and Rare Diseases, RNA modifications and cancer, Gene expression and cancer classification, and Genetic and phenotypic traits in livestock.

Some of the recent publications featuring Xihong Lin's work include:

  • Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study (2020, The Lancet Public Health)
  • Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program (2021, Nature)
  • Association of Public Health Interventions With the Epidemiology of the COVID-19 Outbreak in Wuhan, China (2020, JAMA)
  • Federated learning for predicting clinical outcomes in patients with COVID-19 (2021, Nature Medicine)
  • Reconstruction of the full transmission dynamics of COVID-19 in Wuhan (2020, Nature)

Frequent co-authors who have collaborated extensively with Xihong Lin include:

  • Xihao Li
  • Zilin Li
  • Hufeng Zhou
  • Brian E. Cade
  • Ryan Sun

Xihong Lin has published their research in multiple venues, with a notable number of publications appearing in:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Zenodo (CERN European Organization for Nuclear Research)
  • UNC Libraries
  • arXiv (Cornell University)
  • Nature Communications

Among professional recognitions, Xihong Lin was named a Fellow of the American Statistical Association (ASA) in 2000.

Best Publications

  • Rare-Variant Association Testing for Sequencing Data with the Sequence Kernel Association Test

    Michael C. Wu;Seunggeun Lee;Tianxi Cai;Yun Li

  • Quality of life and satisfaction with outcome among prostate-cancer survivors.

    Martin G. Sanda;Rodney L. Dunn;Jeff Michalski;Howard M. Sandler

  • Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study.

    Long H. Nguyen;David A. Drew;Mark S. Graham;Amit D. Joshi

  • Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program.

    Daniel Taliun;Daniel N. Harris;Michael D. Kessler;Jedidiah Carlson;Jedidiah Carlson

  • Association of Public Health Interventions With the Epidemiology of the COVID-19 Outbreak in Wuhan, China.

    An Pan;Li Liu;Chaolong Wang;Huan Guo

  • LKB1 modulates lung cancer differentiation and metastasis

    Hongbin Ji;Matthew R. Ramsey;D. Neil Hayes;Cheng Fan

  • Rare-variant association analysis: study designs and statistical tests.

    Seunggeung Lee;Gonçalo R. Abecasis;Michael Boehnke;Xihong Lin

  • Optimal unified approach for rare-variant association testing with application to small-sample case-control whole-exome sequencing studies.

    Seunggeun Lee;Mary J. Emond;Michael J. Bamshad;Kathleen C. Barnes

  • Aberrant lipid metabolism disrupts calcium homeostasis causing liver endoplasmic reticulum stress in obesity

    Suneng Fu;Ling Yang;Ping Li;Oliver Hofmann

  • Optimal tests for rare variant effects in sequencing association studies.

    Seunggeun Lee;Michael C. Wu;Xihong Lin

  • Inference in generalized additive mixed modelsby using smoothing splines

    Xihong Lin;Daowen Zhang

  • Powerful SNP-set analysis for case-control genome-wide association studies.

    Michael C. Wu;Peter Kraft;Michael P. Epstein;Deanne M. Taylor

  • Federated learning for predicting clinical outcomes in patients with COVID-19.

    Ittai Dayan;Holger R. Roth;Aoxiao Zhong;Ahmed Harouni

  • Bias correction in generalised linear mixed models with a single component of dispersion

    Norman E. Breslow;Xihong Lin

  • Bias Correction in Generalized Linear Mixed Models with Multiple Components of Dispersion

    Xihong Lin;Norman E. Breslow

  • Sequence kernel association tests for the combined effect of rare and common variants.

    Iuliana Ionita-Laza;Seunggeun Lee;Vlad Makarov;Joseph D. Buxbaum

  • Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

    Daniel Taliun;Daniel N. Harris;Michael D. Kessler;Jedidiah Carlson;Jedidiah Carlson

  • Control for Population Structure and Relatedness for Binary Traits in Genetic Association Studies via Logistic Mixed Models

    Han Chen;Chaolong Wang;Matthew P. Conomos;Adrienne M. Stilp

  • ACAT: A Fast and Powerful p Value Combination Method for Rare-Variant Analysis in Sequencing Studies.

    Yaowu Liu;Sixing Chen;Zilin Li;Alanna C. Morrison

  • Impact of Physician Asthma Care Education on Patient Outcomes

    Michael D. Cabana;Kathryn K. Slish;David Evans;Robert B. Mellins

  • Variance component testing in generalised linear models with random effects

    Xihong Lin

  • Nonparametric Function Estimation for Clustered Data When the Predictor is Measured without/with Error

    Xihong Lin;Raymond J. Carroll

  • Semiparametric Stochastic Mixed Models for Longitudinal Data

    Daowen Zhang;Xihong Lin;Jonathan Raz;Maryfran Sowers

Frequent Co-Authors

David C. Christiani
David C. Christiani Harvard University
Susan Redline
Susan Redline Brigham and Women's Hospital
Andrea Baccarelli
Andrea Baccarelli Columbia University
Geoffrey Liu
Geoffrey Liu Princess Margaret Cancer Centre
Richa Saxena
Richa Saxena Harvard University
Eric Boerwinkle
Eric Boerwinkle The University of Texas Health Science Center at Houston
Matthew H. Kulke
Matthew H. Kulke Boston Medical Center
Joel Schwartz
Joel Schwartz Harvard University
Daniel J. Gottlieb
Daniel J. Gottlieb Brigham and Women's Hospital
Raymond J. Carroll
Raymond J. Carroll Texas A&M University

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