World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
5804
World Ranking
11225
National Ranking
185

Overview

Martin Krallinger is affiliated with the Barcelona Supercomputing Center in Spain. Their research primarily focuses on the intersection of computer science and biomedical applications, especially in the fields of artificial intelligence and molecular biology.

The scientist's work spans various topics, which include:

  • Biomedical Text Mining and Ontologies
  • Natural Language Processing Techniques
  • Topic Modeling
  • Linguistics and Terminology Studies
  • Semantic Web and Ontologies
  • Spanish Linguistics and Language Studies
  • Text Readability and Simplification

The main fields of study associated with Martin Krallinger are:

  • Computer Science

Within these fields, they have contributed significantly to several subfields, including:

  • Artificial Intelligence
  • Molecular Biology
  • Language and Linguistics
  • General Health Professions
  • Sociology and Political Science

Frequent collaborators in their research include:

  • Antonio Miranda-Escalada
  • Eulàlia Farré-Maduell
  • Salvador Lima López
  • Luis Gascó
  • Vicent Brivá-Iglesias

Martin Krallinger has published extensively in venues such as:

  • Zenodo (CERN European Organization for Nuclear Research)
  • OPAL (Open@LaTrobe) (La Trobe University)
  • arXiv (Cornell University)
  • Database
  • Nature Reviews Materials

Recent publications authored or co-authored by Martin Krallinger include:

  • Redefining biomaterial biocompatibility: challenges for artificial intelligence and text mining (2023, Trends in Biotechnology)
  • Time to kick-start text mining for biomaterials (2020, Nature Reviews Materials)
  • Overview of DrugProt task at BioCreative VII: data and methods for large-scale text mining and knowledge graph generation of heterogenous chemical-protein relations (2023, Database)
  • The Devices, Experimental Scaffolds, and Biomaterials Ontology (DEB): A Tool for Mapping, Annotation, and Analysis of Biomaterials Data (2020, Advanced Functional Materials)
  • Challenges and opportunities for mining adverse drug reactions: perspectives from pharma, regulatory agencies, healthcare providers and consumers (2022, Database)

Best Publications

  • The CHEMDNER corpus of chemicals and drugs and its annotation principles.

    Martin Krallinger;Obdulia Rabal;Florian Leitner;Miguel Vazquez

  • Overview of the protein-protein interaction annotation extraction task of BioCreative II

    Martin Krallinger;Florian Leitner;Carlos Rodriguez-Penagos;Alfonso Valencia

  • Information retrieval and text mining technologies for chemistry

    Martin Krallinger;Obdulia Rabal;Anália Lourenço;Anália Lourenço;Julen Oyarzabal

  • Linking genes to literature: text mining, information extraction, and retrieval applications for biology

    Martin Krallinger;Alfonso Valencia;Lynette Hirschman

  • CHEMDNER: The drugs and chemical names extraction challenge

    Martin Krallinger;Florian Leitner;Obdulia Rabal;Miguel Vazquez

  • Text-mining and information-retrieval services for molecular biology

    Martin Krallinger;Alfonso Valencia

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

    Martin Krallinger;Alexander Morgan;Larry Smith;Florian Leitner

  • Text-mining approaches in molecular biology and biomedicine

    Martin Krallinger;Ramon Alonso-Allende Erhardt;Alfonso Valencia

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

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

  • Text mining for the biocuration workflow

    Lynette Hirschman;Gully A. P. C. Burns;Martin Krallinger;Cecilia Arighi

  • 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

  • Evaluation of BioCreAtIvE assessment of task 2.

    Christian Blaschke;Eduardo Andres Leon;Martin Krallinger;Alfonso Valencia

  • An Overview of BioCreative II.5

    Florian Leitner;Scott A. Mardis;Martin Krallinger;Gianni Cesareni

  • Text mining for biology - the way forward: opinions from leading scientists

    Russ B. Altman;Casey M. Bergman;Judith A. Blake;Christian Blaschke

  • Overview of the BioCreative III Workshop

    Cecilia N. Arighi;Zhiyong Lu;Martin Krallinger;Kevin Bretonnel Cohen

  • Text Mining for Metabolic Pathways, Signaling Cascades, and Protein Networks

    Robert Hoffmann;Martin Krallinger;Eduardo Andres;Javier Tamames

  • Overview of the CLEF eHealth Evaluation Lab 2020

    Lorraine Goeuriot;Hanna Suominen;Hanna Suominen;Hanna Suominen;Liadh Kelly;Antonio Miranda-Escalada

  • Text Mining for Drugs and Chemical Compounds: Methods, Tools and Applications

    Miguel Vazquez;Martin Krallinger;Florian Leitner;Alfonso Valencia

  • Analysis of biological processes and diseases using text mining approaches.

    Martin Krallinger;Florian Leitner;Alfonso Valencia

  • BioCreative III interactive task: an overview.

    Cecilia N Arighi;Phoebe M Roberts;Shashank Agarwal;Sanmitra Bhattacharya

Frequent Co-Authors

Lynette Hirschman
Lynette Hirschman Mitre (United States)
Zhiyong Lu
Zhiyong Lu National Institutes of Health
Georgios Paliouras
Georgios Paliouras National Centre of Scientific Research Demokritos
Andrew Chatr-aryamontri
Andrew Chatr-aryamontri University of Montreal
Cathy H. Wu
Cathy H. Wu University of Delaware
Florentino Fdez-Riverola
Florentino Fdez-Riverola Universidade de Vigo
W. John Wilbur
W. John Wilbur National Institutes of Health
Cecilia N. Arighi
Cecilia N. Arighi University of Delaware
Gianni Cesareni
Gianni Cesareni University of Rome Tor Vergata
Maria-Pau Ginebra
Maria-Pau Ginebra Universitat Politècnica de Catalunya

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