ReviewExpert opinion on drug discovery2012
Computational analysis of high-throughput flow cytometry data.
Review in Expert opinion on drug discovery, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 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
22 citing papers in PubMed.
- Artificial Intelligence in Haematologic Diagnostics: Current Applications and Future Perspectives.Acta haematologica · 2026Review
- Comparative analysis between zebrafish and an automated live-cell assay to classify developmental neurotoxicant chemicals.Toxicology and applied pharmacology · 2023Article
- Best practices for reporting throughput in biomedical research.Nature methods · 2022Article
- The effects of incubation media on the assessment of the shape of human erythrocytes by flow cytometry: a contribution to mathematical data interpretation to enable wider application of the method.European biophysics journal : EBJ · 2021Article
- Computational methods for characterizing and learning from heterogeneous cell signaling data.Current opinion in systems biology · 2021Article
- Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition).European journal of immunology · 2019Article
- Single-cell technologies in reproductive immunology.American journal of reproductive immunology (New York, N.Y. : 1989) · 2019Review
- Data-Driven Flow Cytometry Analysis.Methods in molecular biology (Clifton, N.J.) · 2019Review
- Guidelines for the use of flow cytometry and cell sorting in immunological studies.European journal of immunology · 2017Article
- Of Cytometry, Stem Cells and Fountain of Youth.Stem cell reviews and reports · 2017Review
- Automated Assessment of Disease Progression in Acute Myeloid Leukemia by Probabilistic Analysis of Flow Cytometry Data.IEEE transactions on bio-medical engineering · 2017Article
- Antibody Engineering for Pursuing a Healthier Future.Frontiers in microbiology · 2017Review
- Deep profiling of multitube flow cytometry data.Bioinformatics (Oxford, England) · 2015Article
- ISAC's classification results file format.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2015Article
- A non-parametric Bayesian model for joint cell clustering and cluster matching: identification of anomalous sample phenotypes with random effects.BMC bioinformatics · 2014Article
- How to build a time-gated luminescence microscope.Current protocols in cytometry · 2014Article
- Article
- Single cell spectroscopy: noninvasive measures of small-scale structure and function.Methods (San Diego, Calif.) · 2013Review
- Multiparameter flow cytometry: advances in high resolution analysis.Immune network · 2013Article
- High-throughput secondary screening at the single-cell level.Journal of laboratory automation · 2013Article
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.
Funding
Abstract
introductionFlow cytometry has been around for over 40 years, but only recently has the opportunity arisen to move into the high-throughput domain. The technology is now available and is highly competitive with imaging tools under the right conditions. Flow cytometry has, however, been a technology that has focused on its unique ability to study single cells and appropriate analytical tools are readily available to handle this traditional role of the technology. AREAS COVERED: Expansion of flow cytometry to a high-throughput (HT) and high-content technology requires both advances in hardware and analytical tools. The historical perspective of flow cytometry operation as well as how the field has changed and what the key changes have been discussed. The authors provide a background and compelling arguments for moving toward HT flow, where there are many innovative opportunities. With alternative approaches now available for flow cytometry, there will be a considerable number of new applications. These opportunities show strong capability for drug screening and functional studies with cells in suspension. EXPERT OPINION: There is no doubt that HT flow is a rich technology awaiting acceptance by the pharmaceutical community. It can provide a powerful phenotypic analytical toolset that has the capacity to change many current approaches to HT screening. The previous restrictions on the technology, based on its reduced capacity for sample throughput, are no longer a major issue. Overcoming this barrier has transformed a mature technology into one that can focus on systems biology questions not previously considered possible.
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.