World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
11719
World Ranking
6098
National Ranking
2744

Overview

W. John Wilbur is affiliated with the National Institutes of Health in the United States. Their research spans multiple fields including Computer Science, Biochemistry, Genetics and Molecular Biology, as well as Medicine. The main areas of study focus on Artificial Intelligence, Molecular Biology, Genetics, Health Informatics, and Infectious Diseases.

The scientist's work covers several specific topics, with notable concentration in:

  • Topic Modeling
  • Biomedical Text Mining and Ontologies
  • Machine Learning in Healthcare
  • Artificial Intelligence in Healthcare and Education
  • Natural Language Processing Techniques
  • Race, Genetics, and Society
  • Forensic and Genetic Research

W. John Wilbur has published research in multiple venues, frequently contributing to:

  • Bioinformatics
  • arXiv (Cornell University)
  • The American Journal of Human Genetics
  • BMC Medical Informatics and Decision Making
  • Journal of the American Medical Informatics Association

Selected recent papers by Wilbur include:

  • MedCPT: Contrastive Pre-trained Transformers with large-scale PubMed search logs for zero-shot biomedical information retrieval, 2023, Bioinformatics
  • Evolving use of ancestry, ethnicity, and race in genetics research-A survey spanning seven decades, 2021, The American Journal of Human Genetics
  • Deep learning with sentence embeddings pre-trained on biomedical corpora improves the performance of finding similar sentences in electronic medical records, 2020, BMC Medical Informatics and Decision Making
  • Better synonyms for enriching biomedical search, 2020, Journal of the American Medical Informatics Association
  • MedCPT: Contrastive Pre-trained Transformers with Large-scale PubMed Search Logs for Zero-shot Biomedical Information Retrieval, 2023, arXiv (Cornell University)

Frequent co-authors include:

  • Zhiyong Lu
  • Qingyu Chen
  • Donald C. Comeau
  • Lana Yeganova
  • Qiao Jin

Best Publications

  • Database resources of the National Center for Biotechnology Information

    Unknown

  • Overview of BioCreative II gene mention recognition

    Larry Smith;Lorraine K Tanabe;Rie Johnson nee Ando;Cheng-Ju Kuo

  • Tagging gene and protein names in biomedical text.

    Lorraine K. Tanabe;W. John Wilbur

  • The automatic identification of stop words

    W. John Wilbur;Karl Sirotkin

  • GeneWays: a system for extracting, analyzing, visualizing, and integrating molecular pathway data

    Andrey Rzhetsky;Ivan Iossifov;Tomohiro Koike;Michael Krauthammer

  • GENETAG: a tagged corpus for gene/protein named entity recognition.

    Lorraine K. Tanabe;Natalie Xie;Lynne H. Thom;Wayne Matten

  • PubMed related articles: a probabilistic topic-based model for content similarity.

    Jimmy J. Lin;Jimmy J. Lin;W. John Wilbur

  • MedPost: a part-of-speech tagger for bioMedical text

    L. Smith;T. Rindflesch;W. J. Wilbur

  • SplicePort—An interactive splice-site analysis tool

    Rezarta Islamaj Dogan;Lise Getoor;W. John Wilbur;Stephen M. Mount

  • Evaluation of query expansion using MeSH in PubMed

    Zhiyong Lu;Won Kim;W. John Wilbur

  • Evaluation of text-mining systems for biology: overview of the Second BioCreative community challenge

    Martin Krallinger;Alexander Morgan;Larry Smith;Florian Leitner

  • Genes, Themes, and Microarrays: Using Information Retrieval for Large-Scale Gene Analysis

    Hagit Shatkay;Stephen Edwards;W. John Wilbur;Mark Boguski

  • The NLM Indexing Initiative.

    Alan R. Aronson;Olivier Bodenreider;H. Florence Chang;Susanne M. Humphrey

  • New directions in biomedical text annotation: definitions, guidelines and corpus construction

    W John Wilbur;Andrey Rzhetsky;Hagit Shatkay

  • BioC: a minimalist approach to interoperability for biomedical text processing

    Donald C. Comeau;Rezarta Islamaj Doğan;Paolo Ciccarese;Kevin Bretonnel Cohen

  • Extracting drug-drug interactions from literature using a rich feature-based linear kernel approach

    Sun Kim;Haibin Liu;Lana Yeganova;W. John Wilbur

  • The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text

    Martin Krallinger;Miguel Vazquez;Florian Leitner;David Salgado

  • Modelling neutral and selective evolution of protein folding.

    David J. Lipman;W. John Wilbur

  • The gene normalization task in BioCreative III

    Zhiyong Lu;Hung-Yu Kao;Chih-Hsuan Wei;Minlie Huang

  • Multi-dimensional classification of biomedical text

    Hagit Shatkay;Fengxia Pan;Andrey Rzhetsky;W. John Wilbur

  • An analysis of statistical term strength and its use in the indexing and retrieval of molecular biology texts.

    W.John Wilbur;Yiming Yang;Yiming Yang

  • Database resources of the National Center for Biotechnology Information

    Unknown

Frequent Co-Authors

Zhiyong Lu
Zhiyong Lu National Institutes of Health
Jimmy Lin
Jimmy Lin University of Waterloo
Martin Krallinger
Martin Krallinger Barcelona Supercomputing Center
Cathy H. Wu
Cathy H. Wu University of Delaware
Karin Verspoor
Karin Verspoor RMIT University
Hong-Jie Dai
Hong-Jie Dai Southwest University
Alan R. Aronson
Alan R. Aronson National Institutes of Health
Dina Demner-Fushman
Dina Demner-Fushman National Institutes of Health
Hong Yu
Hong Yu University of Massachusetts Lowell
Andrew Chatr-aryamontri
Andrew Chatr-aryamontri University of Montreal

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