DeepQA statistics

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Citations per year

Number of citations per year for the bioinformatics software tool DeepQA
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Tool usage distribution map

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DeepQA specifications

Information


Unique identifier OMICS_14121
Name DeepQA
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Perl
Computer skills Advanced
Stability No
Maintained Yes

Versioning


No version available

Maintainer


Publication for DeepQA

DeepQA citations

 (2)
library_books

An overview of comparative modelling and resources dedicated to large scale modelling of genome sequences

2017
Acta Crystallogr D Struct Biol
PMCID: 5571743
PMID: 28777078
DOI: 10.1107/S2059798317008920

[…] t al., 2012). The recent ProQ3 uses a deep-learning method to combine ProQ2 with Rosetta energy terms (Leaver-Fay et al., 2011) and has been shown to be superior to ProQ2 (Uziela et al., 2016, 2017). DeepQA is another deep-learning method that combines physiochemical properties (i.e. secondary-structure similarity and solvent accessibility) and statistical potential energy terms (Cao et al., 2016) […]

library_books

Rare disease diagnosis: A review of web search, social media and large scale data mining approaches

2015
PMCID: 4590007
PMID: 26442199
DOI: 10.1080/21675511.2015.1083145

[…] greatest players of all time, Ken Jennings and Brad Rutter in a televised match in February 2011.The success of Watson prompted IBM to put the question-answering technology underlying Watson (called DeepQA) to other uses. Computationally, answering a question in a game of Jeopardy! is very similar to the task of compiling a differential diagnosis: Based on a natural language query (e.g., “Jewish […]


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DeepQA institution(s)
Department of Computer Science, Pacific Lutheran University, Tacoma, WA, USA; Department of Electrical Engineering and Computer Science, Wichita State University, Wichita, KS, USA; Department of Computer Science, University of Missouri, Columbia, MO, USA; Informatics Institute, University of Missouri, Columbia, MO, USA
DeepQA funding source(s)
This work was supported by the NIH (grant n°R01GM093123).

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