Fluidigm is a Molecular and Single Cell Biology company that creates microfluidic-based chips and instrumentation for Life-Science research.
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Vizgen webinar: spatial relationships in Developmental Biology
Nov 21, 2023
MERFISH integrates spatial transcriptomics technology with high resolution spatial imaging, In this webinar we will...
Nov 14, 2023
The xCELLigence RTCA eSight enables simultaneous real time biosensor impedance-based and...
NanoCellect webinar: Plant Potential - Gentle Cell Sorting for Enhanced Plant Biology Workflows
Nov 3, 2023
Gentle cell sorting is a useful tool to increase the efficiency of plant biology workflows that include gene...
Single Cell Deposition: the cornerstone of Flow Cytometry for cellular analysis and manipulation
Nov 2, 2023
One notable technology for harnessing the power of single cell deposition is the NanoCellect WOLF G2 Cell Sorter and N1...
RareCyte webinar recording: Use of open-source software for quantitative analysis of multiplex image
Nov 1, 2023
In this webinar, Dr. McArdle describes how multiplex immunostaining is a key method for understanding spatial context...
Emulate in vivo conditions – introduce shear flow to your experiments with BioFlux system
Oct 31, 2023
Most research is still conducted in vitro without the presence of flow. We use the BioFlux System to give you the...
Single Cell Deposition: the cornerstone of Flow Cytometry for cellular analysis and manipulation
Oct 30, 2023
One notable technology for harnessing the power of single cell deposition is the NanoCellect WOLF G2 Cell Sorter and N1...
Validation of an orthotopic non-small cell lung cancer mouse model to use in radiotherapy studies
Oct 30, 2023
The use of pre-clinical orthotopic mouse models is essential for the development of novel therapies targeting solid...
Analysis of single-cell transcriptomes in colorectal cancer
Feb 21, 2017
Scientists performed an unbiased analysis of functional diversity in colorectal cancer cells and their microenvironment using RNA-seq profiling of over 1,500 unsorted single cells from 11 primary tumors and matched normal mucosa (NM). To robustly interpret single-cell transcriptomes, we developed novel algorithms for normalizing expression estimates (pQ), clustering cells (RCA) and identifying differentially expressed genes (NODES). RCA identified 6 major cell types and multiple subtypes within colorectal samples.
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