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Chapter
Federated Learning over Harmonized Data Silos
Federated Learning is a distributed machine learning approach that enables geographically distributed data silos to collaboratively learn a joint machine learning model without sharing data. Most of the existi...
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Chapter and Conference Paper
Towards Sparsified Federated Neuroimaging Models via Weight Pruning
Federated training of large deep neural networks can often be restrictive due to the increasing costs of communicating the updates with increasing model sizes. Various model pruning techniques have been design...
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Article
Open AccessNERO: a biomedical named-entity (recognition) ontology with a large, annotated corpus reveals meaningful associations through text embedding
Machine reading (MR) is essential for unlocking valuable knowledge contained in millions of existing biomedical documents. Over the last two decades1,2, the most dramatic advances in MR have followed in the wake ...
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Article
Open AccessRapid detection of identity-by-descent tracts for mega-scale datasets
The ability to identify segments of genomes identical-by-descent (IBD) is a part of standard workflows in both statistical and population genetics. However, traditional methods for finding local IBD across all...
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Chapter and Conference Paper
NSEEN: Neural Semantic Embedding for Entity Normalization
Much of human knowledge is encoded in text, available in scientific publications, books, and the web. Given the rapid growth of these resources, we need automated methods to extract such knowledge into machine...
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Chapter and Conference Paper
Abstract Meaning Representations as Linked Data
The complex relationship between natural language and formal semantic representations can be investigated by the development of large, semantically-annotated corpora. The “Abstract Meaning Representation” (AMR...
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Chapter and Conference Paper
Leveraging Linked Data to Discover Semantic Relations Within Data Sources
Map** data to a shared domain ontology is a key step in publishing semantic content on the Web. Most of the work on automatically map** structured and semi-structured sources to ontologies focuses on seman...
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Chapter and Conference Paper
Finding Concept Coverings in Aligning Ontologies of Linked Data
Despite the recent growth in the size of the Linked Data Cloud, the absence of links between the vocabularies of the sources has resulted in heterogenous schemas. Our previous work tried to find conceptual map...
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Article
No evidence of interaction between known lipid-associated genetic variants and smoking in the multi-ethnic PAGE population
Genome-wide association studies (GWAS) have identified many variants that influence high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and/or triglycerides. However, environmental modif...
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Article
Open AccessGenetic variants associated with fasting glucose and insulin concentrations in an ethnically diverse population: results from the Population Architecture using Genomics and Epidemiology (PAGE) study
Multiple genome-wide association studies (GWAS) within European populations have implicated common genetic variants associated with insulin and glucose concentrations. In contrast, few studies have been conduc...
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Chapter and Conference Paper
A Graph-Based Approach to Learn Semantic Descriptions of Data Sources
Semantic models of data sources and services provide support to automate many tasks such as source discovery, data integration, and service composition, but writing these semantic descriptions by hand is a ted...
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Article
Open AccessA ν-support vector regression based approach for predicting imputation quality
Decades of genome-wide association studies (GWAS) have accumulated large volumes of genomic data that can potentially be reused to increase statistical power of new studies, but different genoty** platforms ...
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Chapter and Conference Paper
Semi-automatically Map** Structured Sources into the Semantic Web
Linked data continues to grow at a rapid rate, but a limitation of a lot of the data that is being published is the lack of a semantic description. There are tools, such as D2R, that allow a user to quickly co...
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Chapter and Conference Paper
Discovering Concept Coverings in Ontologies of Linked Data Sources
Despite the increase in the number of linked instances in the Linked Data Cloud in recent times, the absence of links at the concept level has resulted in heterogenous schemas, challenging the interoperability...
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Chapter and Conference Paper
Rapidly Integrating Services into the Linked Data Cloud
The amount of data available in the Linked Data cloud continues to grow. Yet, few services consume and produce linked data. There is recent work that allows a user to define a linked service from an online ser...
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Chapter and Conference Paper
Linking and Building Ontologies of Linked Data
The Web of Linked Data is characterized by linking structured data from different sources using equivalence statements, such as owl:sameAs, as well as other types of linked properties. The ontologies behind th...
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Chapter and Conference Paper
Automatically Constructing Semantic Web Services from Online Sources
The work on integrating sources and services in the Semantic Web assumes that the data is either already represented in RDF or OWL or is available through a Semantic Web Service. In practice, there is a tremen...
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Chapter and Conference Paper
Automatically Composing Data Workflows with Relational Descriptions and Shim Services
Many scientific problems can be represented as computational workflows of operations that access remote data, integrate heterogeneous data, and analyze and derive new data. Even when the data access and proces...
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Article
Composing, optimizing, and executing plans for bioinformatics web services
The emergence of a large number of bioinformatics datasets on the Internet has resulted in the need for flexible and efficient approaches to integrate information from multiple bioinformatics data sources and ...
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Chapter and Conference Paper
Integration of Heterogeneous Knowledge Sources in the CALO Query Manager
We report on our effort to build a real system for integrating heterogeneous knowledge sources with different query answering and reasoning capabilities. We are conducting this work in the context of CALO (Cog...
