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Michael R. Berthold

Michael R. Berthold

D-Index & Metrics

Computer Science

D-Index
33
Citations
11282
World Ranking
12373
National Ranking
605

Research.com Recognitions

  • 2011 - IEEE Fellow For contributions to approximate learning algorithms for life science data mining
  • 2008 - ACM Senior Member

Overview

Michael R. Berthold is affiliated with the University of Konstanz in Germany. Their research spans multiple fields, with a strong focus on computer science and its intersections with biological sciences and business disciplines.

The primary fields of study for Michael R. Berthold include:

  • Computer Science
  • Biochemistry, Genetics and Molecular Biology
  • Business, Management and Accounting

Within these broader fields, they have contributed to several subfields such as:

  • Artificial Intelligence
  • Molecular Biology
  • Computer Networks and Communications
  • Management Information Systems
  • Biophysics

Their main research topics cover areas including:

  • Machine Learning and Data Classification
  • Advanced Database Systems and Queries
  • Big Data and Business Intelligence
  • Cell Image Analysis Techniques
  • Genetics, Bioinformatics, and Biomedical Research
  • Scientific Computing and Data Management
  • Epigenetics and DNA Methylation

Michael R. Berthold has published in a variety of academic venues, reflecting a diverse range of research focuses:

  • Frontiers in Computer Science
  • Angewandte Chemie International Edition
  • Data Mining and Knowledge Discovery
  • arXiv (Cornell University)
  • Frontiers in Bioinformatics

Their recent papers include:

  • "Integration of the ImageJ Ecosystem in KNIME Analytics Platform" (2020), Frontiers in Computer Science
  • "A DNA Polymerase Variant Senses the Epigenetic Marker 5-Methylcytosine by Increased Misincorporation" (2024), Angewandte Chemie International Edition
  • "Widening: using parallel resources to improve model quality" (2021), Data Mining and Knowledge Discovery
  • "SciJava Ops: An Improved Algorithms Framework for Fiji and Beyond" (2024), arXiv (Cornell University)
  • "SciJava Ops: an improved algorithms framework for Fiji and beyond" (2024), Frontiers in Bioinformatics

The scientist has collaborated frequently with several coauthors, indicating sustained partnerships over multiple projects. Notable frequent coauthors include:

  • Frank Klawonn
  • Rosaria Silipo
  • Christian Borgelt
  • Frank Höppner
  • Curtis Rueden

Michael R. Berthold has also contributed to academic literature through book publications with reputable publishers such as Springer. Their books include:

  • Advances in Intelligent Data Analysis XVIII (2020), Springer Science+Business Media
  • Guide to Intelligent Data Science (2020), Springer International Publishing

Recognition for their work includes distinctions such as being named an IEEE Fellow in 2011 for contributions to approximate learning algorithms for life science data mining and status as an ACM Senior Member since 2008.

Best Publications

  • KNIME - the Konstanz information miner: version 2.0 and beyond

    Michael R. Berthold;Nicolas Cebron;Fabian Dill;Thomas R. Gabriel

  • KNIME: The Konstanz Information Miner

    Michael R. Berthold;Nicolas Cebron;Fabian Dill;Thomas R. Gabriel

  • Biological imaging software tools

    Kevin W. Eliceiri;Michael R. Berthold;Ilya G. Goldberg;Luis Ibáñez

  • Position paper: The coming of age of artificial intelligence in medicine

    Vimla L. Patel;Edward H. Shortliffe;Mario Stefanelli;Peter Szolovits

  • Mining molecular fragments: finding relevant substructures of molecules

    C. Borgelt;M.R. Berthold

  • Intelligent Data Analysis: An Introduction

    Michael Berthold;David J. Hand

  • Advances in intelligent data analysis

    David J. Hand;Douglas H. Fisher;Michael R. Berthold

  • Guide to Intelligent Data Analysis: How to Intelligently Make Sense of Real Data

    Michael R. Berthold;Christian Borgelt;Frank Hppner;Frank Klawonn

  • Constructive training of probabilistic neural networks

    Michael R. Berthold;Jay Diamond

  • KNIME for reproducible cross-domain analysis of life science data

    Alexander Fillbrunn;Christian Dietz;Julianus Pfeuffer;René Rahn

  • KNIME-CDK: Workflow-driven cheminformatics.

    Stephan Beisken;Thorsten Meinl;Bernd Wiswedel;Luis F. de Figueiredo

  • Boosting the Performance of RBF Networks with Dynamic Decay Adjustment

    Michael R. Berthold;Jay Diamond

  • OpenML: A collaborative science platform

    Jan van Rijn;Bernd Bischl;Luis Torgo;Bo Gao

  • Mixed fuzzy rule formation

    Michael R. Berthold

  • Building precise classifiers with automatic rule extraction

    K.-P. Huber;M.R. Berthold

  • Computational life sciences II

    Michael R. Berthold;Robert C. Glen;Kay Diederichs;Oliver Kohlbacher

  • Towards creative information exploration based on koestler's concept of bisociation

    Werner Dubitzky;Tobias Kötter;Oliver Schmidt;Michael R. Berthold

  • A time delay radial basis function network for phoneme recognition

    M.R. Berthold

  • KNIME for Open-Source Bioimage Analysis: A Tutorial.

    Christian Dietz;Michael R. Berthold

  • Visualizing fuzzy points in parallel coordinates

    M.R. Berthold;L.O. Hall

  • Whither Systems Medicine

    Rolf Apweiler;Tim Beissbarth;Michael R. Berthold;Nils Blüthgen

  • Missing values and learning of fuzzy rules

    Michael R. Berthold;Klaus-Peter Huber

Frequent Co-Authors

Paul R. Cohen
Paul R. Cohen University of Pittsburgh
David J. Hand
David J. Hand Imperial College London
Xiaohui Liu
Xiaohui Liu Brunel University London
Alexander Bürkle
Alexander Bürkle University of Konstanz
Rudolf Kruse
Rudolf Kruse Otto-von-Guericke University Magdeburg
Robert F. Murphy
Robert F. Murphy Carnegie Mellon University
Anne E. Carpenter
Anne E. Carpenter Broad Institute
Marcel Leist
Marcel Leist University of Konstanz
Kay Diederichs
Kay Diederichs University of Konstanz
Oliver Kohlbacher
Oliver Kohlbacher University of Tübingen

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