Evidence map›Paper›PMID 28849569›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2017

Comprehensive Analyses of Tissue-Specific Networks with Implications to Psychiatric Diseases.

Guan Ning Lin, Roser Corominas, Hyun-Jun Nam, Jorge Urresti, Lilia M Iakoucheva

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Insight into the structures of Interleukin-18 systems.Computational biology and chemistry · 2020
    Article
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.

Guan Ning LinDepartment of Psychiatry, University of California San Diego, 9500 Gilman Drive #0603, La Jolla, CA, 92093, USA.
Roser CorominasDepartment of Psychiatry, University of California San Diego, 9500 Gilman Drive #0603, La Jolla, CA, 92093, USA.
Hyun-Jun NamDepartment of Psychiatry, University of California San Diego, 9500 Gilman Drive #0603, La Jolla, CA, 92093, USA.
Jorge UrrestiDepartment of Psychiatry, University of California San Diego, 9500 Gilman Drive #0603, La Jolla, CA, 92093, USA.
Lilia M IakouchevaDepartment of Psychiatry, University of California San Diego, 9500 Gilman Drive #0603, La Jolla, CA, 92093, USA. lilyak@ucsd.edu.

Funding

Integrative functional genomic study of pathways impacted by recurrent autism CNVR01MH108528 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI IAKOUCHEVA, LILIA M, MUOTRI, ALYSSON R. · 2016 to 2020
$2.6M
Evaluating the effect of splicing mutations on isoform networks in autismR01MH109885 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI IAKOUCHEVA, LILIA M, MUOTRI, ALYSSON R. · 2016 to 2020
$2.5M
A computational framework for predicting the impact of mutations in autismR01MH105524 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI IAKOUCHEVA, LILIA M, RADIVOJAC, PREDRAG · 2014 to 2016
$1.4M
A systems biology approach to unravel theunderlying functional modules of ASDR01HD065288 · NICHD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI IAKOUCHEVA, LILIA M · 2009 to 2010
$1.3M
Protein network of high risk copy number variants for psychiatric disordersR21MH104766 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI IAKOUCHEVA, LILIA M · 2014 to 2015
$421k
NICHD NIH HHS R01 HD065288NIMH NIH HHS R01 MH105524NIMH NIH HHS R01 MH108528NIMH NIH HHS R01 MH109885NIMH NIH HHS R21 MH104766
6 · The paper itself

Abstract

Recent advances in genome sequencing and "omics" technologies are opening new opportunities for improving diagnosis and treatment of human diseases. The precision medicine initiative in particular aims at developing individualized treatment options that take into account individual variability in genes and environment of each person. Systems biology approaches that group genes, transcripts and proteins into functionally meaningful networks will play crucial role in the future of personalized medicine. They will allow comparison of healthy and disease-affected tissues and organs from the same individual, as well as between healthy and disease-afflicted individuals. However, the field faces a multitude of challenges ranging from data integration to statistical and combinatorial issues in data analyses. This chapter describes computational approaches developed by us and the others to tackle challenges in tissue-specific network analyses, with the main focus on psychiatric diseases.

Indexed as

Gene Regulatory NetworksHumansMental DisordersMutationOrgan SpecificityPrecision MedicineProtein Interaction MappingSystems BiologyAlternatively spliced isoformsAutismCopy number variantsDe novo mutationsGene expressionGeneticsNetwork analysesProtein–protein interactionsPsychiatric diseasesSystems biology

Identifiers

PMID28849569
PMCPMC5699888

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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.