ArticleGenome biology2016
AirLab: a cloud-based platform to manage and share antibody-based single-cell research.
Article in Genome biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed, 26 citations in OpenAlex.
- Trial
- A tumor profiling resource for ovarian cancer: insights into chemotherapy-driven heterogeneity and personalized treatment strategy.Nature communications · 2026Article
- Article
- Single-cell proteomics defines the cellular heterogeneity of localized prostate cancer.Cell reports. Medicine · 2022Article
- Mass cytometric and transcriptomic profiling of epithelial-mesenchymal transitions in human mammary cell lines.Scientific data · 2022Article
- Profound dysregulation of T cell homeostasis and function in patients with severe COVID-19.Allergy · 2021Article
- Multi-omics reveals clinically relevant proliferative drive associated with mTOR-MYC-OXPHOS activity in chronic lymphocytic leukemia.Nature cancer · 2021Article
- Digital Management Systems in Academic Health Sciences Laboratories: A Scoping Review.Healthcare (Basel, Switzerland) · 2021Article
- A distinct innate immune signature marks progression from mild to severe COVID-19.Cell reports. Medicine · 2021Article
- Imaging mass cytometry and multiplatform genomics define the phenogenomic landscape of breast cancer.Nature cancer · 2020Article
- Compensation of Signal Spillover in Suspension and Imaging Mass Cytometry.Cell systems · 2018Article
- histoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data.Nature methods · 2017Article
- 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
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell analysis technologies are essential tools in research and clinical diagnostics. These methods include flow cytometry, mass cytometry, and other microfluidics-based technologies. Most laboratories that employ these methods maintain large repositories of antibodies. These ever-growing collections of antibodies, their multiple conjugates, and the large amounts of data generated in assays using specific antibodies and conditions makes a dedicated software solution necessary. We have developed AirLab, a cloud-based tool with web and mobile interfaces, for the organization of these data. AirLab streamlines the processes of antibody purchase, organization, and storage, antibody panel creation, results logging, and antibody validation data sharing and distribution. Furthermore, AirLab enables inventory of other laboratory stocks, such as primers or clinical samples, through user-controlled customization. Thus, AirLab is a mobile-powered and flexible tool that harnesses the capabilities of mobile tools and cloud-based technology to facilitate inventory and sharing of antibody and sample collections and associated validation 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.