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Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case
BACKGROUND: We address the goal of curating observations from published experiments in a generalizable form; reasoning over these observations to generate interpretations and then querying this interpreted knowledge to supply the supporting evidence. We present web-application software as part of th...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3176268/ https://www.ncbi.nlm.nih.gov/pubmed/21859449 http://dx.doi.org/10.1186/1471-2105-12-351 |
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author | Russ, Thomas A Ramakrishnan, Cartic Hovy, Eduard H Bota, Mihail Burns, Gully APC |
author_facet | Russ, Thomas A Ramakrishnan, Cartic Hovy, Eduard H Bota, Mihail Burns, Gully APC |
author_sort | Russ, Thomas A |
collection | PubMed |
description | BACKGROUND: We address the goal of curating observations from published experiments in a generalizable form; reasoning over these observations to generate interpretations and then querying this interpreted knowledge to supply the supporting evidence. We present web-application software as part of the 'BioScholar' project (R01-GM083871) that fully instantiates this process for a well-defined domain: using tract-tracing experiments to study the neural connectivity of the rat brain. RESULTS: The main contribution of this work is to provide the first instantiation of a knowledge representation for experimental observations called 'Knowledge Engineering from Experimental Design' (KEfED) based on experimental variables and their interdependencies. The software has three parts: (a) the KEfED model editor - a design editor for creating KEfED models by drawing a flow diagram of an experimental protocol; (b) the KEfED data interface - a spreadsheet-like tool that permits users to enter experimental data pertaining to a specific model; (c) a 'neural connection matrix' interface that presents neural connectivity as a table of ordinal connection strengths representing the interpretations of tract-tracing data. This tool also allows the user to view experimental evidence pertaining to a specific connection. BioScholar is built in Flex 3.5. It uses Persevere (a noSQL database) as a flexible data store and PowerLoom(® )(a mature First Order Logic reasoning system) to execute queries using spatial reasoning over the BAMS neuroanatomical ontology. CONCLUSIONS: We first introduce the KEfED approach as a general approach and describe its possible role as a way of introducing structured reasoning into models of argumentation within new models of scientific publication. We then describe the design and implementation of our example application: the BioScholar software. This is presented as a possible biocuration interface and supplementary reasoning toolkit for a larger, more specialized bioinformatics system: the Brain Architecture Management System (BAMS). |
format | Online Article Text |
id | pubmed-3176268 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-31762682011-09-20 Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case Russ, Thomas A Ramakrishnan, Cartic Hovy, Eduard H Bota, Mihail Burns, Gully APC BMC Bioinformatics Software BACKGROUND: We address the goal of curating observations from published experiments in a generalizable form; reasoning over these observations to generate interpretations and then querying this interpreted knowledge to supply the supporting evidence. We present web-application software as part of the 'BioScholar' project (R01-GM083871) that fully instantiates this process for a well-defined domain: using tract-tracing experiments to study the neural connectivity of the rat brain. RESULTS: The main contribution of this work is to provide the first instantiation of a knowledge representation for experimental observations called 'Knowledge Engineering from Experimental Design' (KEfED) based on experimental variables and their interdependencies. The software has three parts: (a) the KEfED model editor - a design editor for creating KEfED models by drawing a flow diagram of an experimental protocol; (b) the KEfED data interface - a spreadsheet-like tool that permits users to enter experimental data pertaining to a specific model; (c) a 'neural connection matrix' interface that presents neural connectivity as a table of ordinal connection strengths representing the interpretations of tract-tracing data. This tool also allows the user to view experimental evidence pertaining to a specific connection. BioScholar is built in Flex 3.5. It uses Persevere (a noSQL database) as a flexible data store and PowerLoom(® )(a mature First Order Logic reasoning system) to execute queries using spatial reasoning over the BAMS neuroanatomical ontology. CONCLUSIONS: We first introduce the KEfED approach as a general approach and describe its possible role as a way of introducing structured reasoning into models of argumentation within new models of scientific publication. We then describe the design and implementation of our example application: the BioScholar software. This is presented as a possible biocuration interface and supplementary reasoning toolkit for a larger, more specialized bioinformatics system: the Brain Architecture Management System (BAMS). BioMed Central 2011-08-22 /pmc/articles/PMC3176268/ /pubmed/21859449 http://dx.doi.org/10.1186/1471-2105-12-351 Text en Copyright © 2011 Russ et al; licensee BioMed Central Ltd. https://creativecommons.org/licenses/by/2.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0 (https://creativecommons.org/licenses/by/2.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Russ, Thomas A Ramakrishnan, Cartic Hovy, Eduard H Bota, Mihail Burns, Gully APC Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case |
title | Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case |
title_full | Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case |
title_fullStr | Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case |
title_full_unstemmed | Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case |
title_short | Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case |
title_sort | knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3176268/ https://www.ncbi.nlm.nih.gov/pubmed/21859449 http://dx.doi.org/10.1186/1471-2105-12-351 |
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