ReviewGenomics, proteomics & bioinformatics2019
Translational Informatics for Parkinson's Disease: from Big Biomedical Data to Small Actionable Alterations.
Review in Genomics, proteomics & bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed, 35 citations in OpenAlex.
- NDDRF 2.0: An update and expansion of risk factor knowledge base for personalized prevention of neurodegenerative diseases.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Deciphering shared molecular dysregulation across Parkinson's disease variants using a multi-modal network-based data integration and analysis.NPJ Parkinson's disease · 2025Article
- Translational Informatics for Neuropharmacology: Databases, Ontologies, and Analytics.Current neuropharmacology · 2025Article
- Conventional and Emerging Drug Targeting Sites in Alzheimer's Disease and the Role of Translational Informatics in its Diagnosis and Management.Current neuropharmacology · 2025Review
- Translational Informatics Driven Drug Repositioning for Neurodegenerative Disease.Current neuropharmacology · 2025Review
- How Lifetime Evolution of Parkinson's Disease Could Shape Clinical Trial Design: A Shared Patient-Clinician Viewpoint.Brain sciences · 2024Article
- Challenges and best practices for digital unstructured data enrichment in health research: A systematic narrative review.PLOS digital health · 2023Article
- From multi-omics approaches to personalized medicine in myocardial infarction.Frontiers in cardiovascular medicine · 2023Review
- The evolution of Big Data in neuroscience and neurology.Journal of big data · 2023Article
- NDDRF: A risk factor knowledgebase for personalized prevention of neurodegenerative diseases.Journal of advanced research · 2022Article
- Multivariate competing endogenous RNA network characterization for cancer microRNA biomarker discovery: a novel bioinformatics model with application to prostate cancer metastasis.Precision clinical medicine · 2022Article
- Multi-omics network characterization reveals novel microRNA biomarkers and mechanisms for diagnosis and subtyping of kidney transplant rejection.Journal of translational medicine · 2021Article
- The fourth scientific discovery paradigm for precision medicine and healthcare: Challenges ahead.Precision clinical medicine · 2021Article
- Translational Informatics for Natural Products as Antidepressant Agents.Frontiers in cell and developmental biology · 2021Review
- MIKB: A manually curated and comprehensive knowledge base for myocardial infarction.Computational and structural biotechnology journal · 2021Article
- The Combination of Tradition and Future: Data-Driven Natural-Product-Based Treatments for Parkinson's Disease.Evidence-based complementary and alternative medicine : eCAM · 2021Review
- Systems biology comprehensive analysis on breast cancer for identification of key gene modules and genes associated with TNM-based clinical stages.Scientific reports · 2020Article
- Data-driven translational prostate cancer research: from biomarker discovery to clinical decision.Journal of translational medicine · 2020Review
- Big Data and the Brain: Peeking at the Future.Genomics, proteomics & bioinformatics · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Parkinson's disease (PD) is a common neurological disease in elderly people, and its morbidity and mortality are increasing with the advent of global ageing. The traditional paradigm of moving from small data to big data in biomedical research is shifting toward big data-based identification of small actionable alterations. To highlight the use of big data for precision PD medicine, we review PD big data and informatics for the translation of basic PD research to clinical applications. We emphasize some key findings in clinically actionable changes, such as susceptibility genetic variations for PD risk population screening, biomarkers for the diagnosis and stratification of PD patients, risk factors for PD, and lifestyles for the prevention of PD. The challenges associated with the collection, storage, and modelling of diverse big data for PD precision medicine and healthcare are also summarized. Future perspectives on systems modelling and intelligent medicine for PD monitoring, diagnosis, treatment, and healthcare are discussed in the end.
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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.