ArticleJournal of translational medicine2014
Single-cell transcriptome in the identification of disease biomarkers: opportunities and challenges.
Article in Journal of translational medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 14 citations in OpenAlex.
- Polar Gini Curve: A Technique to Discover Gene Expression Spatial Patterns from Single-cell RNA-seq Data.Genomics, proteomics & bioinformatics · 2021Article
- An integrative systems biology approach for precision medicine in diabetic kidney disease.Diabetes, obesity & metabolism · 2018Review
- Next-generation molecular diagnosis: single-cell sequencing from bench to bedside.Cellular and molecular life sciences : CMLS · 2017Review
- Microfluidic approaches to synchrotron radiation-based Fourier transform infrared (SR-FTIR) spectral microscopy of living biosystems.Protein and peptide letters · 2016Article
- Enhanced frequency and potential mechanism of B regulatory cells in patients with lung cancer.Journal of translational medicine · 2014Article
- Single-cell transcriptomics: an emerging tool in the study of cardiometabolic disease.Journal of translational medicine · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single cell transcriptome defined as the entire RNA or polyadenylated products of RNA polymerase II on a cell can describe the gene regulation networks responsible for physiological functions, behaviours, and phenotypes in response to signals and microenvironmental changes. Single cell transcriptome/sequencing has the special power to investigate small groups of differentiating cells, circulating tumour cells, or tissue stem cells. A large number of factors may influence the extent of single-cell heterogeneity within a system. It is the opportunity that the single-cell sequencing can be used for the identification of genetic changes in rare cells, e.g. cancer and tissue stem cells, in clinical samples. The methodologies of single-cell sequencing have been improved and developed with the increase of the understanding and attention. The clinical research and application of the single cell sequencing analysis are expected to identify and validate disease-specific biomarkers, network biomarkers, dynamic network biomarkers. The single cell research and value will be also dependent upon the understanding of genomic heterogeneity, planning and design of study protocol, representative of selected and targeted cells, and sensitivity and repeatability of the methodology. The single cell sequencing can be used to develop new diagnostics, monitor disease progresses, measure responses to therapies, and predict the prognosis of patients, although there are still a large number of challenges and difficulties to be faced. It would be more values and specificities of the single cell sequencing to integrate with the function of cells, organs, and systems of the body, the clinical phenotypes of patients, and the description of clinical bioinformatics.
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.