Data Integration in the Life Sciences

This book constitutes the proceedings of the 11th International Conference on Data Integration in the Life Sciences, DILS 2015, held in Los Angeles, CA, USA, in July 2015.

The 24 papers presented in this volume were carefully reviewed and selected from 40 submissions. They are organized in topical sections named: data integration technologies; ontology and knowledge engineering for data integration; biomedical data standards and coding; medical research applications; and graduate student consortium.

Inhalt

Data Integration Technologies.- Combining Multiple Knowledge Sources: A Case Study of Drug Induced Liver Injury.- Vidal, Elena Zotkina, and Louiqa Raschid GEM: The GAAIN Entity Mapper.- Data Integration in the Human Brain Project.- SchizConnect: Virtual Data Integration in Neuroimaging.- Ontology and Knowledge Engineering for Data Integration Annotating Medical Forms Using UMLS.- OnSim: A Similarity Measure for Determining Relatedness Between Ontology Terms.- AnnEvol: An Evolutionary Framework to Description Ontology-Based Annotations.- Terminology Development Towards Harmonizing Multiple Clinical Neuroimaging Research Repositories.- Creating Biomedical Ontologies Using mOntage.- Creation of Definitions for Ontologies: A Case Study in the Leukemia Domain.- Biomedical Data Standards and Coding Integration of Hematopoietic Cell Transplantation Outcomes Data: Data Standards Are Not Enough.- ICD Code Retrieval: Novel Approach for Assisted Disease Classification.- Medical Research Applications.- Integration of Multimodal Neuroimaging and Electroencephalography for the Study of Acute Epileptiform Activity After Traumatic Brain Injury.- SVI: A Simple Single-Nucleotide Human Variant Interpretation Tool for Clinical Use.- Quality Control Considerations for the Effective Integration of Neuroimaging Data.- Integration of Behavioral, Structural, Functional, and Genetic Data for the Study of Autism Spectrum Disorders.- Reverse Engineering Measures of Clinical Care Quality: Sequential Pattern Mining.- Inference and Verification of Probabilistic Graphical Models from High-Dimensional Data.- SPIRIT-ML: A Machine Learning Platform for Deriving Knowledge from Biomedical Datasets.- Demonstration: Mining Sentence and Annotation Evidence for a Cross Genome Study of the Plant Hormone Ethylene.- Graduate Student Consortium.- GAAIN Virtual Appliances: Virtual Machine Technology for Scientific Data Analysis.- The GAAIN Entity Mapper: Towards Practical Medical Informatics Application.- Efficient Management of Cached Data in the Global Alzheimer's Association Interactive Network.- Domain Specific Document Retrieval Framework for Real-Time Social Health Data.