Literature DB >> 22616108

ApiNATOMY: a novel toolkit for visualizing multiscale anatomy schematics with phenotype-related information.

Bernard de Bono1, Pierre Grenon, Stephen John Sammut.   

Abstract

A significant proportion of biomedical resources carries information that cross references to anatomical structures across multiple scales. To improve the visualization of such resources in their anatomical context, we developed an automated methodology that produces anatomy schematics in a consistent manner,and provides for the overlay of anatomy-related resource information onto the same diagram. This methodology, called ApiNATOMY, draws upon the topology of ontology graphs to automatically lay out treemaps representing body parts as well as semantic metadata linking to such ontologies. More generally, ApiNATOMY treemaps provide an efficient and manageable way to visualize large biomedical ontologies in a meaningful and consistent manner. In the anatomy domain, such treemaps will allow epidemiologists, clinicians, and biomedical scientists to review, and interact with, anatomically aggregated heterogeneous data and model resources. Such an approach supports the visual identification of functional relations between anatomically colocalized resources that may not be immediately amenable to automation by ontology-based inferencing. We also describe the application of ApiNATOMY schematics to integrate, and add value to, human phenotype-related information—results are found at http://apinatomy.org. The long-term goal for the ApiNATOMY toolkit is to support clinical and scientific graphical user interfaces and dashboards for biomedical resource management and data analytics. (c) 2012 Wiley Periodicals, Inc.

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Mesh:

Year:  2012        PMID: 22616108     DOI: 10.1002/humu.22065

Source DB:  PubMed          Journal:  Hum Mutat        ISSN: 1059-7794            Impact factor:   4.878


  14 in total

1.  A physiome interoperability roadmap for personalized drug development.

Authors:  Simon Thomas; Katherine Wolstencroft; Bernard de Bono; Peter J Hunter
Journal:  Interface Focus       Date:  2016-04-06       Impact factor: 3.906

2.  Modular modelling with Physiome standards.

Authors:  Michael T Cooling; David P Nickerson; Poul M F Nielsen; Peter J Hunter
Journal:  J Physiol       Date:  2016-08-29       Impact factor: 5.182

3.  Meeting the multiscale challenge: representing physiology processes over ApiNATOMY circuits using bond graphs.

Authors:  B de Bono; S Safaei; P Grenon; P Hunter
Journal:  Interface Focus       Date:  2017-12-15       Impact factor: 3.906

4.  Representing Normal and Abnormal Physiology as Routes of Flow in ApiNATOMY.

Authors:  Bernard de Bono; Tom Gillespie; Monique C Surles-Zeigler; Natallia Kokash; Jeff S Grethe; Maryann Martone
Journal:  Front Physiol       Date:  2022-04-25       Impact factor: 4.755

5.  The Open Physiology workflow: modeling processes over physiology circuitboards of interoperable tissue units.

Authors:  Bernard de Bono; Soroush Safaei; Pierre Grenon; David P Nickerson; Samuel Alexander; Michiel Helvensteijn; Joost N Kok; Natallia Kokash; Alan Wu; Tommy Yu; Peter Hunter; Richard A Baldock
Journal:  Front Physiol       Date:  2015-02-24       Impact factor: 4.566

6.  Implementation of a model of bodily fluids regulation.

Authors:  Julie Fontecave-Jallon; S Randall Thomas
Journal:  Acta Biotheor       Date:  2015-05-03       Impact factor: 1.774

Review 7.  The role of markup for enabling interoperability in health informatics.

Authors:  Steve McKeever; David Johnson
Journal:  Front Physiol       Date:  2015-05-18       Impact factor: 4.566

8.  Eliciting candidate anatomical routes for protein interactions: a scenario from endocrine physiology.

Authors:  Pierre Grenon; Bernard de Bono
Journal:  BMC Bioinformatics       Date:  2013-04-16       Impact factor: 3.169

9.  Functional tissue units and their primary tissue motifs in multi-scale physiology.

Authors:  Bernard de Bono; Pierre Grenon; Richard Baldock; Peter Hunter
Journal:  J Biomed Semantics       Date:  2013-10-08

10.  Integration and Visualization of Translational Medicine Data for Better Understanding of Human Diseases.

Authors:  Venkata Satagopam; Wei Gu; Serge Eifes; Piotr Gawron; Marek Ostaszewski; Stephan Gebel; Adriano Barbosa-Silva; Rudi Balling; Reinhard Schneider
Journal:  Big Data       Date:  2016-06       Impact factor: 2.128

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