ReviewBiomicrofluidics2017
Microfluidics for genome-wide studies involving next generation sequencing.
Review in Biomicrofluidics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- Microsystem Advances through Integration with Artificial Intelligence.Micromachines · 2023Review
- Deep learning in spatial transcriptomics: Learning from the next next-generation sequencing.Biophysics reviews · 2023Review
- A Critical Review on the Sensing, Control, and Manipulation of Single Molecules on Optofluidic Devices.Micromachines · 2022Review
- Liquid Biopsy: A Distinctive Approach to the Diagnosis and Prognosis of Cancer.Cancer informatics · 2022Review
- Microfluidics applications for high-throughput single cell sequencing.Journal of nanobiotechnology · 2021Review
- The future of microfluidics in immune checkpoint blockade.Cancer gene therapy · 2021Review
- Integration of Droplet Microfluidic Tools for Single-Cell Functional Metagenomics: An Engineering Head Start.Genomics, proteomics & bioinformatics · 2021Article
- Microfluidic Platform for Next-Generation Sequencing Library Preparation with Low-Input Samples.Analytical chemistry · 2020Article
- Microfluidic epigenomic mapping technologies for precision medicine.Lab on a chip · 2019Review
- Leveraging machine vision in cell-based diagnostics to do more with less.Nature materials · 2019Article
- Microfluidic Low-Input Fluidized-Bed Enabled ChIP-seq Device for Automated and Parallel Analysis of Histone Modifications.Analytical chemistry · 2018Article
- Cancer Diagnosis Using a Liquid Biopsy: Challenges and Expectations.Diagnostics (Basel, Switzerland) · 2018Review
- Microfluidics-Based Chromosome Conformation Capture (3C) Technology for Examining Chromatin Organization with a Low Quantity of Cells.Analytical chemistry · 2018Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Next-generation sequencing (NGS) has revolutionized how molecular biology studies are conducted. Its decreasing cost and increasing throughput permit profiling of genomic, transcriptomic, and epigenomic features for a wide range of applications. Microfluidics has been proven to be highly complementary to NGS technology with its unique capabilities for handling small volumes of samples and providing platforms for automation, integration, and multiplexing. In this article, we review recent progress on applying microfluidics to facilitate genome-wide studies. We emphasize on several technical aspects of NGS and how they benefit from coupling with microfluidic technology. We also summarize recent efforts on developing microfluidic technology for genomic, transcriptomic, and epigenomic studies, with emphasis on single cell analysis. We envision rapid growth in these directions, driven by the needs for testing scarce primary cell samples from patients in the context of precision medicine.
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.