World's Best Scientists 2026 revealed!
Leming Shi

Leming Shi

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Biology and Biochemistry
China
2023

D-Index & Metrics

Biology and Biochemistry

D-Index
79
Citations
29012
World Ranking
4233
National Ranking
125

Research.com Recognitions

  • 2023 - Research.com Biology and Biochemistry in China Leader Award

Overview

Leming Shi is affiliated with Fudan University in China and contributes extensively to the fields of Biochemistry, Genetics and Molecular Biology, with a focus on subfields including Molecular Biology, Infectious Diseases, Genetics, Pulmonary and Respiratory Medicine, and Electrical and Electronic Engineering.

Their research covers several main topics: Gene expression and cancer classification, Bioinformatics and Genomic Networks, Molecular Biology Techniques and Applications, Genomics and Phylogenetic Studies, COVID-19 Clinical Research Studies, Long-Term Effects of COVID-19, and Inflammasome and immune disorders.

Shi's recent papers include:

  • Blood molecular markers associated with COVID-19 immunopathology and multi-organ damage (2020, The EMBO Journal)
  • Hidden biases in germline structural variant detection (2021, Genome biology)
  • Quartet DNA reference materials and datasets for comprehensively evaluating germline variant calling performance (2023, Genome biology)
  • Towards the development of an omics data analysis framework (2020, Regulatory Toxicology and Pharmacology)
  • Tackling the translational challenges of multi-omics research in the realm of European personalised medicine: A workshop report (2022, Frontiers in Molecular Biosciences)

Frequent coauthors in their work include:

  • Yuanting Zheng
  • Jingcheng Yang
  • Ying Yu
  • Huixiao Hong
  • Andreas Scherer

The scientist's publications have appeared predominantly in these venues:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Genome biology
  • The EMBO Journal
  • Frontiers in Molecular Biosciences
  • EBioMedicine

Best Publications

  • The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

    Leming Shi;Laura H. Reid;Wendell D. Jones;Richard Shippy

  • The Microarray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

    Leming Shi;Gregory Campbell;Wendell D. Jones;Fabien Campagne

  • A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium

    Zhenqiang Su;Paweł P. Łabaj;Sheng Li;Jean Thierry-Mieg

  • The Estrogen Receptor Relative Binding Affinities of 188 Natural and Xenochemicals: Structural Diversity of Ligands

    Robert M. Blair;Hong Fang;William S. Branham;Bruce S. Hass

  • Evaluation of DNA microarray results with quantitative gene expression platforms.

    Roger D Canales;Yuling Luo;James C Willey;Bradley Austermiller

  • Genomic and Transcriptomic Landscape of Triple-Negative Breast Cancers: Subtypes and Treatment Strategies.

    Yi Zhou Jiang;Ding Ma;Chen Suo;Jinxiu Shi

  • Performance comparison of one-color and two-color platforms within the Microarray Quality Control (MAQC) project

    Tucker A Patterson;Edward K Lobenhofer;Stephanie B Fulmer-Smentek;Patrick J Collins

  • Structure-activity relationships for a large diverse set of natural, synthetic, and environmental estrogens.

    Hong Fang;Weida Tong;Leming M. Shi;Robert Blair

  • Telomerase activation by genomic rearrangements in high-risk neuroblastoma

    Martin Peifer;Falk Hertwig;Frederik Roels;Daniel Dreidax

  • The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance

    Charles Wang;Binsheng Gong;Pierre R. Bushel;Jean Thierry-Mieg

  • Rat toxicogenomic study reveals analytical consistency across microarray platforms

    Lei Guo;Edward K Lobenhofer;Charles Wang;Richard Shippy

  • Drug hypersensitivity caused by alteration of the MHC-presented self-peptide repertoire

    David A. Ostrov;Barry J. Grant;Yuri A. Pompeu;John Sidney

  • Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

    Wenqian Zhang;Ying Yu;Falk Hertwig;Falk Hertwig;Jean Thierry-Mieg

  • QSAR models using a large diverse set of estrogens

    Leming M. Shi;Hong Fang;Weida Tong;Jie Wu

  • Detecting and correcting systematic variation in large-scale RNA sequencing data

    Sheng Li;Paweł P Łabaj;Paul Zumbo;Peter Sykacek

  • The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies

    Leming Shi;Wendell D. Jones;Roderick V. Jensen;Stephen C. Harris

  • The External RNA Controls Consortium: a progress report.

    Shawn C Baker;Steven R Bauer;Richard P Beyer;James D Brenton

  • Next-generation sequencing in the clinic: promises and challenges.

    Jiekun Xuan;Ying Yu;Tao Qing;Lei Guo

  • A rat RNA-Seq transcriptomic BodyMap across 11 organs and 4 developmental stages.

    Ying Yu;James C. Fuscoe;Chen Zhao;Chao Guo

  • Similarities and Differences in the Expression of Drug-Metabolizing Enzymes between Human Hepatic Cell Lines and Primary Human Hepatocytes

    Lei Guo;Stacey Dial;Leming Shi;William Branham

Frequent Co-Authors

Weida Tong
Weida Tong National Center for Toxicological Research
Hong Fang
Hong Fang National Center for Toxicological Research
Huixiao Hong
Huixiao Hong United States Food and Drug Administration
Roger Perkins
Roger Perkins United States Food and Drug Administration
Lei Guo
Lei Guo National Center for Toxicological Research
Matthias Fischer
Matthias Fischer University of Cologne
Christopher E. Mason
Christopher E. Mason Cornell University
James C. Willey
James C. Willey University of Toledo
Pierre R. Bushel
Pierre R. Bushel National Institutes of Health
Yuri Nikolsky
Yuri Nikolsky F1 Genomics

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