Data Integration in the Life Sciences

13th International Conference, DILS 2018, Hannover, Germany, November 20-21, 2018, Proceedings

Häftad, Engelska, 2018

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This book constitutes revised selected papers from the 13th International Conference on Data Integration in the Life Sciences, DILS 2018, held in Hannover, Germany, in November 2018.The 5 full, 8 short, 3 poster and 4 demo papers presented in this volume were carefully reviewed and selected from 22 submissions. The papers are organized in topical sections named: big biomedical data integration and management; data exploration in the life sciences; biomedical data analytics; and big biomedical applications.

Produktinformation

Utgivningsdatum2018-12-31
Mått155 x 235 x 13 mm
Vikt359 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Bioinformatics
Antal sidor218
Upplaga18001
FörlagSpringer Nature Switzerland AG
ISBN9783030060152

Tillhör följande kategorier

Tillämpad datateknik inom Data och it
Systemvetenskap och AI inom Data och it
Biovetenskap inom Naturvetenskap och teknik
Artificiell intelligens inom Data och it
Databaser inom Data och it

Big Biomedical Data Integration and Management.- Do Scaling Algorithms Preserve Word2Vec Semantics? A Case Study for Medical Entities.- Combining semantic and lexical measures to evaluate medical terms similarity.- Construction and Visualization of Dynamic Biological Networks: Benchmarking the Neo4J Graph Database.- A Knowledge-driven Pipeline from Transforming Big Data into Actionable Knowledge.- Leaving no stone unturned: Using machine learning based approaches for information extraction from full texts of a research data warehouse.- Data Exploration in the Life Sciences.- Towards research infrastructures that curate scientific information: A use case in life sciences.- Interactive Visualization for large-scale multi-factorial Research Designs.- FedSDM: Semantic Data Manager for Federations of RDF Datasets.- Data Integration for Supporting Biomedical Knowledge Graph Creation at Large-Scale.- DISBi: A flexible framework for integrating systems biology data.- Biomedical Data Analytics.- Using Machine Learning to Distinguish Infected from Non-Infected Subjects at an Early Stage Based on Viral Inoculation.- Automated Coding of Medical Diagnostics from Free-Text: the Role of Parameters Optimization and Imbalanced Classes.- A learning-based approach to combine medical annotation results.- Knowledge Graph Completion to Predict Polypharmacy Side Effects.- Big Biomedical Applications.- Lung Cancer Concept Annotation from Spanish Clinical Narratives.- Linked Data based Multi-Omics Integration and Visualization for Cancer Decision Networks.- The Hannover Medical School Enterprise Clinical Research Data Warehouse: 5 years of experience.- User-Driven Development of a Novel Molecular Tumor Board Support Tool.- Using Semantic Programming for developing a Web Content Management System for semantic Phenotype Data.- Converting Alzheimer's disease map into a heavyweight ontology: a formal network to integrate data.