Evidence map›Paper›PMID 22779059›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2012

An automated bayesian framework for integrative gene expression analysis and predictive medicine.

Neena Parikh, Amin Zollanvari, Gil Alterovitz

Abstract read
PubMed Full text at PMC
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Neena ParikhDepartment of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA;
Amin Zollanvari
Gil Alterovitz

Funding

Automated Integration of Biomedical KnowledgeR01HG004836 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI ALTEROVITZ, GIL · 2009 to 2010
$856k
A Holistic Approach to Information Processing for Biomedical NetworksR00LM009826 · NLM · BOSTON CHILDREN'S HOSPITAL · PI ALTEROVITZ, GIL · 2010 to 2012
$727k
Beyond Association: Predictive Modeling of Nicotine DependanceR21DA025168 · NIDA · BRIGHAM AND WOMEN'S HOSPITAL · PI ALTEROVITZ, GIL · 2008 to 2009
$350k
NHGRI NIH HHS R01 HG004836NIDA NIH HHS R21 DA025168NLM NIH HHS R00 LM009826
6 · The paper itself

Abstract

motivationThis work constructs a closed loop Bayesian Network framework for predictive medicine via integrative analysis of publicly available gene expression findings pertaining to various diseases.

resultsAn automated pipeline was successfully constructed. Integrative models were made based on gene expression data obtained from GEO experiments relating to four different diseases using Bayesian statistical methods. Many of these models demonstrated a high level of accuracy and predictive ability. The approach described in this paper can be applied to any complex disorder and can include any number and type of genome-scale studies.

Indexed as

Bayesian NetworkGene Expression OmnibusIntegrative GenomicsMulti-network Model

Identifiers

PMID22779059
PMCPMC3392067

What OpenQuestion holds

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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.