ReviewBriefings in bioinformatics2019
Translational bioinformatics in mental health: open access data sources and computational biomarker discovery.
Review in Briefings in bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed.
- Seasonal Restructuring of Microbial Communities and Resistomes in the Shitalakshya River, Bangladesh Revealed by Shotgun Metagenomics.MicrobiologyOpen · 2026Article
- Translational significance of neurodevelopment underpinned 'neurophysiological-cognitive' biomarkers in schizophrenia.Indian journal of psychiatry · 2025Article
- Article
- Translational bioinformatics and data science for biomarker discovery in mental health: an analytical review.Briefings in bioinformatics · 2024Review
- Biomarkers as Biomedical Bioindicators: Approaches and Techniques for the Detection, Analysis, and Validation of Novel Biomarkers of Diseases.Pharmaceutics · 2023Review
- Opportunities for improving data sharing and FAIR data practices to advance global mental health.Global mental health (Cambridge, England) · 2023Review
- Integrative omics of schizophrenia: from genetic determinants to clinical classification and risk prediction.Molecular psychiatry · 2022Review
- MENDA: a comprehensive curated resource of metabolic characterization in depression.Briefings in bioinformatics · 2020Article
- Fostering precision psychiatry through bioinformatics.Revista brasileira de psiquiatria (Sao Paulo, Brazil : 1999)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Mental illness is increasingly recognized as both a significant cost to society and a significant area of opportunity for biological breakthrough. As -omics and imaging technologies enable researchers to probe molecular and physiological underpinnings of multiple diseases, opportunities arise to explore the biological basis for behavioral health and disease. From individual investigators to large international consortia, researchers have generated rich data sets in the area of mental health, including genomic, transcriptomic, metabolomic, proteomic, clinical and imaging resources. General data repositories such as the Gene Expression Omnibus (GEO) and Database of Genotypes and Phenotypes (dbGaP) and mental health (MH)-specific initiatives, such as the Psychiatric Genomics Consortium, MH Research Network and PsychENCODE represent a wealth of information yet to be gleaned. At the same time, novel approaches to integrate and analyze data sets are enabling important discoveries in the area of mental and behavioral health. This review will discuss and catalog into an organizing framework the increasingly diverse set of MH data resources available, using schizophrenia as a focus area, and will describe novel and integrative approaches to molecular biomarker discovery that make use of mental health data.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.