Evidence map›Paper›PMID 27896988›Full record

ArticlePacific Symposium on Biocomputing. Pacific Symposium on Biocomputing2017

PRECISION MEDICINE: DATA AND DISCOVERY FOR IMPROVED HEALTH AND THERAPY.

Alexander A Morgan, Dana C Crawford, Josh C Denny, Sean D Mooney, Bruce J Aronow, Steven E Brenner

Abstract read
In one paragraph

Article in Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

6 authors.

Alexander A MorganStanford University School of Medicine, Stanford, CA 94305, USA, alexmo@stanford.edu.
Dana C Crawford
Josh C Denny
Sean D Mooney
Bruce J Aronow
Steven E Brenner

Funding

Sequencing of Newborn Blood Spot DNA to Improve and Expand Newborn ScreeningU19HD077627 · NICHD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KOENIG, BARBARA A., KWOK, PUI-YAN · 2013 to 2018
$6.6M
Newborn Screening for T-Cell Disorders: Spectrum and OutcomesR01AI105776 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BRENNER, STEVEN E, CHURCH, JOSEPH · 2013 to 2016
$2.4M
Component 2 - Resource ProjectU41HG007346 · NHGRI · UNIVERSITY OF CALIFORNIA BERKELEY · PI BRENNER, STEVEN E · 2015 to 2017
$1.7M
NHGRI NIH HHS U41 HG007346NIAID NIH HHS R01 AI105776NICHD NIH HHS U19 HD077627
6 · The paper itself

Abstract

The major goal of precision medicine is to improve human health. A feature that unites much research in the field is the use of large datasets such as genomic data and electronic health records. Research in this field includes examination of variation in the core bases of DNA and their methylation status, through variations in metabolic and signaling molecules, all the way up to broader systems level changes in physiology and disease presentation. Intermediate goals include understanding the individual drivers of disease that differentiate the cause of disease in each individual. To match this development of approaches to physical and activitybased measurements, computational approaches to using these new streams of data to better understand improve human health are being rapidly developed by the thriving biomedical informatics research community. This session of the 2017 Pacific Symposium of Biocomputing presents some of the latest advances in the capture, analysis and use of diverse biomedical data in precision medicine.

Indexed as

Computational BiologyCongresses as TopicDatabases, FactualElectronic Health RecordsGenomicsHumansPrecision Medicine

Identifiers

PMID27896988
PMCPMC6192531

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.