Formal Methods for the Analysis of Biomedical Ontologies / by Guo-Qiang Zhang, Rashmie Abeysinghe, Licong Cui.

Format:

Book

Author/Creator:

Zhang, Guo-Qiang.

Contributor:

Abeysinghe, Rashmie.

Cui, Licong.

Series:

Synthesis Lectures on Data, Semantics, and Knowledge, 2691-2031

Language:

English

Subjects (All):

Quantitative research.

Medicine--Research.

Medicine.

Biology--Research.

Biology.

Information retrieval.

Computer architecture.

Artificial intelligence--Data processing.

Artificial intelligence.

Ontology.

Data Analysis and Big Data.

Biomedical Research.

Data Storage Representation.

Data Science.

Artificial Intelligence.

Local Subjects:

Data Analysis and Big Data.

Biomedical Research.

Data Storage Representation.

Data Science.

Artificial Intelligence.

Ontology.

Physical Description:

1 online resource (286 pages)

Edition:

2nd ed. 2026.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2026.

Summary:

This book explores the application of formal methods, rooted in mathematics and logic, to the analysis and enhancement of biomedical ontologies. The authors take a pragmatic approach focused on generating actionable insights to achieve high-quality codified biomedical knowledge in the most active and impactful areas where ontologies have a direct real-world impact. The book first introduces simple, yet formalized strategies for discovering undesired and incoherent patterns in ontologies before exploring the application of formal concept analysis for semantic completeness. The authors then discuss formal concept analysis as an ontological engineering principle. The book goes on to highlight the power and utility of uncovering non-lattice structure for debugging ontologies. This Second Edition includes a new chapter that covers recent research on leveraging logical definitions for identifying ontological defects. The authors have also added a new chapter on the perspective of using large language models in the ontological analysis work. In addition, this book: Provides actionable insights for improving the quality of biomedical ontologies in research applications Covers a broad range of topics in a clear and accessible style, making it appropriate for a wide range of readers Presents useful tools, rigorous algorithms, and visualized real-world examples for ontological engineering applications.

Contents:

Introduction

Simple Relational Patterns

Formal Concept Analysis and Semantic Completeness

Algorithms for Extracting Non-lattice Substructures

Non-lattice Substructures in Ontological Analysis

Lexical Sequences and Patterns

Leveraging Logical Definitions

Visualization and Retrospective Ground-Truthing

Prospect of Large Language Models for Ontological Analysis

Conclusion.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

3-031-93776-7

OCLC:

1535405839