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Russell Greiner

Russell Greiner

Award Badge
Computer Science
Canada
2025

D-Index & Metrics

Computer Science

D-Index
68
Citations
31302
World Ranking
2030
National Ranking
75

Research.com Recognitions

  • 2025 - Research.com Computer Science in Canada Leader Award
  • 2022 - Research.com Computer Science in Canada Leader Award

Overview

Russell Greiner is affiliated with the University of Alberta in Canada. Their research output concentrates primarily on medicine, with a significant focus on molecular biology, artificial intelligence, radiology, nuclear medicine, imaging, cardiology, cardiovascular medicine, and epidemiology.

The scientist's work encompasses several main research topics including machine learning in healthcare, COVID-19 diagnosis using AI, COVID-19 epidemiological studies, metabolomics and mass spectrometry studies, ECG monitoring and analysis, data-driven disease surveillance, and computational drug discovery methods.

Frequent coauthors collaborating with Russell Greiner include Andrew J. Greenshaw, Sunil V. Kalmady, Bo Cao, David S. Wishart, and Padma Kaul.

The most common venues for publication are:

  • arXiv (Cornell University)
  • Scientific Reports
  • bioRxiv (Cold Spring Harbor Laboratory)
  • PLoS ONE
  • Canadian Medical Association Journal

Recent papers authored or coauthored by Russell Greiner cover diverse topics related to metabolomics, machine learning, and chemical data analysis. Notable publications include:

  • HMDB 5.0: the Human Metabolome Database for 2022, 2021, published in Nucleic Acids Research
  • CFM-ID 4.0: More Accurate ESI-MS/MS Spectral Prediction and Compound Identification, 2021, published in Analytical Chemistry
  • BioTransformer 3.0-a web server for accurately predicting metabolic transformation products, 2022, published in Nucleic Acids Research
  • Implementing machine learning in medicine, 2021, published in Canadian Medical Association Journal
  • CFM-ID 4.0 - a web server for accurate MS-based metabolite identification, 2022, published in Nucleic Acids Research

Best Publications

  • HMDB: The human metabolome database

    David S. Wishart;Dan Tzur;Craig Knox;Roman Eisner

  • HMDB 3.0—The Human Metabolome Database in 2013

    David S. Wishart;Timothy Jewison;Anchi Guo;Michael Wilson

  • HMDB: a knowledgebase for the human metabolome

    David S. Wishart;Craig Knox;Anchi Guo;Roman Eisner

  • The Human Serum Metabolome

    Nikolaos Psychogios;David D. Hau;Jun Peng;An Chi Guo

  • ClassyFire: automated chemical classification with a comprehensive, computable taxonomy

    Yannick Djoumbou Feunang;Roman Eisner;Craig Knox;Leonid Chepelev

  • Learning Bayesian networks from data: an information-theory based approach

    Jie Cheng;Russell Greiner;Jonathan Kelly;David Bell

  • Comparing Bayesian network classifiers

    Jie Cheng;Russell Greiner

  • CFM-ID: a web server for annotation, spectrum prediction and metabolite identification from tandem mass spectra

    Felicity Allen;Allison Pon;Michael Wilson;Russell Greiner

  • A correction to the algorithm in Reiter's theory of diagnosis

    Russell Greiner;Barbara A. Smith;Ralph W. Wilkerson

  • Competitive fragmentation modeling of ESI-MS/MS spectra for putative metabolite identification

    Felicity Allen;Russell Greiner;David S. Wishart

  • Predicting subcellular localization of proteins using machine-learned classifiers

    Z. Lu;D. Szafron;R. Greiner;P. Lu

  • BioTransformer: a comprehensive computational tool for small molecule metabolism prediction and metabolite identification.

    Yannick Djoumbou-Feunang;Jarlei Fiamoncini;Jarlei Fiamoncini;Alberto Gil-de-la-Fuente;Russell Greiner

  • Investigations of the effects of gender, diurnal variation, and age in human urinary metabolomic profiles.

    Carolyn M. Slupsky;Kathryn N. Rankin;James Wagner;Hao Fu

  • Learning Bayesian Belief Network Classifiers: Algorithms and System

    Jie Cheng;Russell Greiner

  • BASys: a web server for automated bacterial genome annotation.

    Gary H. Van Domselaar;Paul Stothard;Savita Shrivastava;Joseph A. Cruz

  • CFM-ID 4.0: More Accurate ESI-MS/MS Spectral Prediction and Compound Identification.

    Fei Wang;Jaanus Liigand;Jaanus Liigand;Siyang Tian;David Arndt

  • Accurate, fully-automated NMR spectral profiling for metabolomics.

    Siamak Ravanbakhsh;Philip Liu;Trent C. Bjordahl;Rupasri Mandal

  • Structural Extension to Logistic Regression: Discriminative Parameter Learning of Belief Net Classifiers

    Russell Greiner;Xiaoyuan Su;Bin Shen;Wei Zhou

  • Learning cost-sensitive active classifiers

    Russell Greiner;Adam J. Grove;Dan Roth

  • Learning by understanding analogies

    Russell Greiner

Frequent Co-Authors

David S. Wishart
David S. Wishart University of Alberta
Dale Schuurmans
Dale Schuurmans University of Alberta
Tingshao Zhu
Tingshao Zhu University of Chinese Academy of Sciences
Duane Szafron
Duane Szafron University of Alberta
Lihong Li
Lihong Li Amazon (United States)
Xin-Min Li
Xin-Min Li University of Alberta
Vickie E. Baracos
Vickie E. Baracos University of Alberta
Mark Schmidt
Mark Schmidt University of British Columbia
Csaba Szepesvári
Csaba Szepesvári University of Alberta
Eleni Stroulia
Eleni Stroulia University of Alberta

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