ArticleHigh-throughput2018
The High-Throughput Analyses Era: Are We Ready for the Data Struggle?
Article in High-throughput, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 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
36 citing papers in PubMed.
- The importance of cross-talk in research and the body: An early career researcher perspective.Experimental physiology · 2026Article
- Bacterial Siderophore Production in Metal-Rich Environments: Underexplored Sources of Siderophores and Insights into Bioremediation.Journal of natural products · 2026Review
- MicroRNA‑microbiome cross‑kingdom networks drive inflammatory bowel disease through dynamic regulatory ecosystems (Review).International journal of molecular medicine · 2026Review
- Genetic Landscape of Familial Melanoma.Genes · 2025Review
- My friend MIROSLAV: A hackable open-source hardware and software platform for high-throughput monitoring of rodent activity in the home cage.Behavior research methods · 2025Article
- Deep Genomics: Deep Learning-Based Analysis of Genome-Sequenced Data for Identification of Gene Alterations.Methods in molecular biology (Clifton, N.J.) · 2025Article
- A survey of k-mer methods and applications in bioinformatics.Computational and structural biotechnology journal · 2024Review
- "Re-evaluation of variants of uncertain significance in patients with hereditary arrhythmogenic disorders".BMC cardiovascular disorders · 2024Article
- Insight into the Functional Dynamics and Challenges of Exosomes in Pharmaceutical Innovation and Precision Medicine.Pharmaceutics · 2024Review
- Review
- Can I benefit from laboratory automation? A decision aid for the successful introduction of laboratory automation.Analytical and bioanalytical chemistry · 2024Article
- Article
- Editorial: Whole Genome Sequencing for rare diseases.Frontiers in medicine · 2023Article
- Treasures from trash in cancer research.Oncotarget · 2022Article
- Machine learning-based detection of label-free cancer stem-like cell fate.Scientific reports · 2022Article
- Article
- Exploration of biomarkers for the diagnosis, treatment and prognosis of cervical cancer: a review.Discover oncology · 2022Review
- The Breast Cancer Protooncogenes HER2, BRCA1 and BRCA2 and Their Regulation by the iNOS/NOS2 Axis.Antioxidants (Basel, Switzerland) · 2022Review
- Article
- Current Updates on Expanded Carrier Screening: New Insights in the Omics Era.Medicina (Kaunas, Lithuania) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent and rapid technological advances in molecular sciences have dramatically increased the ability to carry out high-throughput studies characterized by big data production. This, in turn, led to the consequent negative effect of highlighting the presence of a gap between data yield and their analysis. Indeed, big data management is becoming an increasingly important aspect of many fields of molecular research including the study of human diseases. Now, the challenge is to identify, within the huge amount of data obtained, that which is of clinical relevance. In this context, issues related to data interpretation, sharing and storage need to be assessed and standardized. Once this is achieved, the integration of data from different -omic approaches will improve the diagnosis, monitoring and therapy of diseases by allowing the identification of novel, potentially actionably biomarkers in view of personalized medicine.
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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.