Evidence map›Paper›PMID 21859449›Full record

ArticleBMC bioinformatics2011

Knowledge engineering tools for reasoning with scientific observations and interpretations: a neural connectivity use case.

Thomas A Russ, Cartic Ramakrishnan, Eduard H Hovy, Mihail Bota, Gully A P C Burns

Abstract read
In one paragraph

Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

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  18. Knowledge synthesis with maps of neural connectivity.Frontiers in neuroinformatics · 2011
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Thomas A RussInformation Sciences Institute, University of Southern California, Marina del Rey, CA, USA.
Cartic Ramakrishnan
Eduard H Hovy
Mihail Bota
Gully A P C Burns

Funding

BIO-INFORMATICS RESEARCH NETWORK COORDINATING CENTER (BIRN-CC)U24RR025736 · NCRR · UNIVERSITY OF SOUTHERN CALIFORNIA · PI KESSELMAN, CARL · 2009 to 2011
$15.0M
Bio-Informatics Research Network Coordinating Center (BIRN-CC)U24GM104203 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI KESSELMAN, CARL · 2012 to 2013
$8.3M
Informatics Infrastructure for vector-based neuroanatomical atlasesR01MH079068 · NIMH · UNIVERSITY OF SOUTHERN CALIFORNIA · PI BURNS, GULLY A. · 2009 to 2013
$1.6M
BioScholar: a Biomedical Knowledge Engineering framework based on the published lR01GM083871 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI BURNS, GULLY A. · 2008 to 2011
$1.0M
NCRR NIH HHS 1 U24 RR025736-01NCRR NIH HHS U24 RR025736NIGMS NIH HHS R01 GM083871NIGMS NIH HHS R01-GM083871NIGMS NIH HHS U24 GM104203NIMH NIH HHS 1R01MH079068-01A2NIMH NIH HHS R01 MH079068
6 · The paper itself

Abstract

backgroundWe 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.

resultsThe 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.

conclusionsWe 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).

Indexed as

Knowledge BasesSoftwareAnimalsBrain MappingComputational BiologyHumansInternetRats

Identifiers

PMID21859449
PMCPMC3176268

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.