Optimization of PACS data persistency using indexed hierarchical data.

We present a new approach for the development of a data persistency layer for a Digital Imaging and Communications in Medicine (DICOM)-compliant Pictu...
689KB Sizes 0 Downloads 0 Views

Recommend Documents

Evaluating the Cassandra NoSQL Database Approach for Genomic Data Persistency.
Rapid advances in high-throughput sequencing techniques have created interesting computational challenges in bioinformatics. One of them refers to management of massive amounts of data generated by automatic sequencers. We need to deal with the persi

DICOM data migration for PACS transition: procedure and pitfalls.
Transition from one Picture Archiving and Communication System (PACS) to the other is costly and disruptive. Especially the migration of the DICOM data from the legacy to the new PACS is a very challenging task, and although such a migration will hap

Towards a semantic PACS: Using Semantic Web technology to represent imaging data.
The DICOM standard is ubiquitous within medicine. However, improved DICOM semantics would significantly enhance search operations. Furthermore, databases of current PACS systems are not flexible enough for the demands within image analysis research.

Optimization of miRNA-seq data preprocessing.
The past two decades of microRNA (miRNA) research has solidified the role of these small non-coding RNAs as key regulators of many biological processes and promising biomarkers for disease. The concurrent development in high-throughput profiling tech

Assessing Dissimilarity Measures for Sample-Based Hierarchical Clustering of RNA Sequencing Data Using Plasmode Datasets.
Sample- and gene-based hierarchical cluster analyses have been widely adopted as tools for exploring gene expression data in high-throughput experiments. Gene expression values (read counts) generated by RNA sequencing technology (RNA-seq) are discre

Detecting disease-associated genomic outcomes using constrained mixture of Bayesian hierarchical models for paired data.
Detecting disease-associated genomic outcomes is one of the key steps in precision medicine research. Cutting-edge high-throughput technologies enable researchers to unbiasedly test if genomic outcomes are associated with disease of interest. However

ANOVA decompositions are a standard method for describing and estimating heterogeneity among the means of a response variable across levels of multiple categorical factors. In such a decomposition, the complete set of main effects and interaction ter

KSC-N: Clustering of Hierarchical Time Profile Data.
Quite a few studies in the behavioral sciences result in hierarchical time profile data, with a number of time profiles being measured for each person under study. Associated research questions often focus on individual differences in profile reperto

Bayesian Hierarchical Model for Differential Gene Expression Using RNA-seq Data.
We introduce model-based Bayesian inference to screen for differentially expressed genes based on RNA-seq data. RNA-seq is a high-throughput next-generation sequencing application that can be used to measure the expression of messenger RNA. We propos

PTHGRN: unraveling post-translational hierarchical gene regulatory networks using PPI, ChIP-seq and gene expression data.
Interactions among transcriptional factors (TFs), cofactors and other proteins or enzymes can affect transcriptional regulatory capabilities of eukaryotic organisms. Post-translational modifications (PTMs) cooperate with TFs and epigenetic alteration