Evidence map›Paper›PMID 26306226›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2015

Novel Application of Junction Trees to the Interpretation of Epigenetic Differences among Lung Cancer Subtypes.

Arturo Lopez Pineda, Vanathi Gopalakrishnan

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Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Arturo Lopez PinedaThe PRoBE Lab, Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA.
Vanathi GopalakrishnanThe PRoBE Lab, Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA.

Funding

Vitamin D3 Modulation of Inflammation and Lung Cancer RiskP50CA090440 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI DACIC, SANJA · 2001 to 2015
$34.6M
Transfer Rule Learning with Functional Mapping for Integrative Modeling of Panomics DataR01GM100387 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI GOPALAKRISHNAN, VANATHI · 2012 to 2018
$1.8M
Bayesian Rule Learning Methods for Disease Prediction and Biomarker DiscoveryR01LM010950 · NLM · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI GOPALAKRISHNAN, VANATHI · 2011 to 2013
$1.1M
NCI NIH HHS P50 CA090440NIGMS NIH HHS R01 GM100387NLM NIH HHS R01 LM010950
6 · The paper itself

Abstract

In this era of precision medicine, understanding the epigenetic differences in lung cancer subtypes could lead to personalized therapies by possibly reversing these alterations. Traditional methods for analyzing microarray data rely on the use of known pathways. We propose a novel workflow, called Junction trees to Knowledge (J2K) framework, for creating interpretable graphical representations that can be derived directly from in silico analysis of microarray data. Our workflow has three steps, preprocessing (discretization and feature selection), construction of a Bayesian network and, its subsequent transformation into a Junction tree. We used data from the Cancer Genome Atlas to perform preliminary analyses of this J2K framework. We found relevant cliques of methylated sites that are junctions of the network along with potential methylation biomarkers in the lung cancer pathogenesis.

Identifiers

PMID26306226
PMCPMC4525224

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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.