microfluidic tissue processor-based Search Results


lateral flow devices  (MicroFluidic Systems)
90
MicroFluidic Systems lateral flow devices
Lateral Flow Devices, supplied by MicroFluidic Systems, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/microfluidic+tissue+processor-based/lateral+flow+devices/pmc08013307-44-107-80
Average 90 stars, based on 1 article reviews
lateral flow devices - by Bioz Stars, 2026-09
90/100 stars
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high throughput microfluidic systems 10x chromium  (MicroFluidic Systems)
90
MicroFluidic Systems high throughput microfluidic systems 10x chromium
Transcriptomic profiling of human and embryonic tissues, experimental animal models and patient-derived cell lines via scRNA-seq enables the study of pancreas progenitors. (1) Single-cell suspensions enter high throughput microfluidic systems (e.g. <t>10X</t> Chromium, Drop-Seq) allowing thousands of cells to be processed and sequenced. (2) Cells undergo dimensionality reduction and are clustered based upon expression profiles – represented via UMAP or t-SNE - enabling the identification of novel cell types and investigation of cellular heterogeneity. (3) Following clustering, differential expression analysis reveals changes in gene expression across cell types. (4) Prediction of cell trajectories can be inferred based upon changes in gene expression over a ‘pseudo’ time-course. Cells are ordered in a 2D space based upon the closeness of their expression pro_les. Overlay of a minimal spanning tree (MST) identifies the longest continual path linking these cells – uncovering cell lineages. (5) Individual trajectories can be dissected and changes in specific gene expression changes plotted in both a supervised and unsupervised manner (6) The development of algorithms (e.g. StemID, SCENT) has enabled the prediction of cell clusters with high potency, stem-like features. Used in conjunction with pseudotime analysis, these algorithms can infer a starting point of differentiation trajectories, as well as identifying novel stem cells in adult tissues.
High Throughput Microfluidic Systems 10x Chromium, supplied by MicroFluidic Systems, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/microfluidic+tissue+processor-based/high+throughput+microfluidic+systems+10x+chromium/pmc08573583-187-31-28
Average 90 stars, based on 1 article reviews
high throughput microfluidic systems 10x chromium - by Bioz Stars, 2026-09
90/100 stars
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microfluidic organotypic device  (BioMimetic Therapeutics)
90
BioMimetic Therapeutics microfluidic organotypic device
Transcriptomic profiling of human and embryonic tissues, experimental animal models and patient-derived cell lines via scRNA-seq enables the study of pancreas progenitors. (1) Single-cell suspensions enter high throughput microfluidic systems (e.g. <t>10X</t> Chromium, Drop-Seq) allowing thousands of cells to be processed and sequenced. (2) Cells undergo dimensionality reduction and are clustered based upon expression profiles – represented via UMAP or t-SNE - enabling the identification of novel cell types and investigation of cellular heterogeneity. (3) Following clustering, differential expression analysis reveals changes in gene expression across cell types. (4) Prediction of cell trajectories can be inferred based upon changes in gene expression over a ‘pseudo’ time-course. Cells are ordered in a 2D space based upon the closeness of their expression pro_les. Overlay of a minimal spanning tree (MST) identifies the longest continual path linking these cells – uncovering cell lineages. (5) Individual trajectories can be dissected and changes in specific gene expression changes plotted in both a supervised and unsupervised manner (6) The development of algorithms (e.g. StemID, SCENT) has enabled the prediction of cell clusters with high potency, stem-like features. Used in conjunction with pseudotime analysis, these algorithms can infer a starting point of differentiation trajectories, as well as identifying novel stem cells in adult tissues.
Microfluidic Organotypic Device, supplied by BioMimetic Therapeutics, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/microfluidic+tissue+processor-based/microfluidic+organotypic+device/10__2903_slash_sp__efsa__2024__en___8597-3005-169-189
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microfluidic organotypic device - by Bioz Stars, 2026-09
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pmma arp 679.04  (Allresist GmbH)
90
Allresist GmbH pmma arp 679.04
Transcriptomic profiling of human and embryonic tissues, experimental animal models and patient-derived cell lines via scRNA-seq enables the study of pancreas progenitors. (1) Single-cell suspensions enter high throughput microfluidic systems (e.g. <t>10X</t> Chromium, Drop-Seq) allowing thousands of cells to be processed and sequenced. (2) Cells undergo dimensionality reduction and are clustered based upon expression profiles – represented via UMAP or t-SNE - enabling the identification of novel cell types and investigation of cellular heterogeneity. (3) Following clustering, differential expression analysis reveals changes in gene expression across cell types. (4) Prediction of cell trajectories can be inferred based upon changes in gene expression over a ‘pseudo’ time-course. Cells are ordered in a 2D space based upon the closeness of their expression pro_les. Overlay of a minimal spanning tree (MST) identifies the longest continual path linking these cells – uncovering cell lineages. (5) Individual trajectories can be dissected and changes in specific gene expression changes plotted in both a supervised and unsupervised manner (6) The development of algorithms (e.g. StemID, SCENT) has enabled the prediction of cell clusters with high potency, stem-like features. Used in conjunction with pseudotime analysis, these algorithms can infer a starting point of differentiation trajectories, as well as identifying novel stem cells in adult tissues.
Pmma Arp 679.04, supplied by Allresist GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/microfluidic+tissue+processor-based/pmma+ar+p+679+04/10__1063_slash_1__5070136-89-7-10
Average 90 stars, based on 1 article reviews
pmma arp 679.04 - by Bioz Stars, 2026-09
90/100 stars
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pet foils  (Coexpan Deutschland)
90
Coexpan Deutschland pet foils
Transcriptomic profiling of human and embryonic tissues, experimental animal models and patient-derived cell lines via scRNA-seq enables the study of pancreas progenitors. (1) Single-cell suspensions enter high throughput microfluidic systems (e.g. <t>10X</t> Chromium, Drop-Seq) allowing thousands of cells to be processed and sequenced. (2) Cells undergo dimensionality reduction and are clustered based upon expression profiles – represented via UMAP or t-SNE - enabling the identification of novel cell types and investigation of cellular heterogeneity. (3) Following clustering, differential expression analysis reveals changes in gene expression across cell types. (4) Prediction of cell trajectories can be inferred based upon changes in gene expression over a ‘pseudo’ time-course. Cells are ordered in a 2D space based upon the closeness of their expression pro_les. Overlay of a minimal spanning tree (MST) identifies the longest continual path linking these cells – uncovering cell lineages. (5) Individual trajectories can be dissected and changes in specific gene expression changes plotted in both a supervised and unsupervised manner (6) The development of algorithms (e.g. StemID, SCENT) has enabled the prediction of cell clusters with high potency, stem-like features. Used in conjunction with pseudotime analysis, these algorithms can infer a starting point of differentiation trajectories, as well as identifying novel stem cells in adult tissues.
Pet Foils, supplied by Coexpan Deutschland, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/microfluidic+tissue+processor-based/pet+foils/10__1063_slash_1__5070136-89-38-43
Average 90 stars, based on 1 article reviews
pet foils - by Bioz Stars, 2026-09
90/100 stars
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digital light processing (dlp)-based 3d bioprinting  (BioMimetic Therapeutics)
90
BioMimetic Therapeutics digital light processing (dlp)-based 3d bioprinting
Transcriptomic profiling of human and embryonic tissues, experimental animal models and patient-derived cell lines via scRNA-seq enables the study of pancreas progenitors. (1) Single-cell suspensions enter high throughput microfluidic systems (e.g. <t>10X</t> Chromium, Drop-Seq) allowing thousands of cells to be processed and sequenced. (2) Cells undergo dimensionality reduction and are clustered based upon expression profiles – represented via UMAP or t-SNE - enabling the identification of novel cell types and investigation of cellular heterogeneity. (3) Following clustering, differential expression analysis reveals changes in gene expression across cell types. (4) Prediction of cell trajectories can be inferred based upon changes in gene expression over a ‘pseudo’ time-course. Cells are ordered in a 2D space based upon the closeness of their expression pro_les. Overlay of a minimal spanning tree (MST) identifies the longest continual path linking these cells – uncovering cell lineages. (5) Individual trajectories can be dissected and changes in specific gene expression changes plotted in both a supervised and unsupervised manner (6) The development of algorithms (e.g. StemID, SCENT) has enabled the prediction of cell clusters with high potency, stem-like features. Used in conjunction with pseudotime analysis, these algorithms can infer a starting point of differentiation trajectories, as well as identifying novel stem cells in adult tissues.
Digital Light Processing (Dlp) Based 3d Bioprinting, supplied by BioMimetic Therapeutics, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/microfluidic+tissue+processor-based/dlp+based+3d+printing/pm32499560-15-152-174
Average 90 stars, based on 1 article reviews
digital light processing (dlp)-based 3d bioprinting - by Bioz Stars, 2026-09
90/100 stars
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cell-laden microfluidic systems  (MicroFluidic Systems)
90
MicroFluidic Systems cell-laden microfluidic systems
Transcriptomic profiling of human and embryonic tissues, experimental animal models and patient-derived cell lines via scRNA-seq enables the study of pancreas progenitors. (1) Single-cell suspensions enter high throughput microfluidic systems (e.g. <t>10X</t> Chromium, Drop-Seq) allowing thousands of cells to be processed and sequenced. (2) Cells undergo dimensionality reduction and are clustered based upon expression profiles – represented via UMAP or t-SNE - enabling the identification of novel cell types and investigation of cellular heterogeneity. (3) Following clustering, differential expression analysis reveals changes in gene expression across cell types. (4) Prediction of cell trajectories can be inferred based upon changes in gene expression over a ‘pseudo’ time-course. Cells are ordered in a 2D space based upon the closeness of their expression pro_les. Overlay of a minimal spanning tree (MST) identifies the longest continual path linking these cells – uncovering cell lineages. (5) Individual trajectories can be dissected and changes in specific gene expression changes plotted in both a supervised and unsupervised manner (6) The development of algorithms (e.g. StemID, SCENT) has enabled the prediction of cell clusters with high potency, stem-like features. Used in conjunction with pseudotime analysis, these algorithms can infer a starting point of differentiation trajectories, as well as identifying novel stem cells in adult tissues.
Cell Laden Microfluidic Systems, supplied by MicroFluidic Systems, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/microfluidic+tissue+processor-based/cell+laden+microfluidic+systems/pm36205119-730-64-24
Average 90 stars, based on 1 article reviews
cell-laden microfluidic systems - by Bioz Stars, 2026-09
90/100 stars
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biomimetic hydrogel microspheres  (BioMimetic Therapeutics)
90
BioMimetic Therapeutics biomimetic hydrogel microspheres
Transcriptomic profiling of human and embryonic tissues, experimental animal models and patient-derived cell lines via scRNA-seq enables the study of pancreas progenitors. (1) Single-cell suspensions enter high throughput microfluidic systems (e.g. <t>10X</t> Chromium, Drop-Seq) allowing thousands of cells to be processed and sequenced. (2) Cells undergo dimensionality reduction and are clustered based upon expression profiles – represented via UMAP or t-SNE - enabling the identification of novel cell types and investigation of cellular heterogeneity. (3) Following clustering, differential expression analysis reveals changes in gene expression across cell types. (4) Prediction of cell trajectories can be inferred based upon changes in gene expression over a ‘pseudo’ time-course. Cells are ordered in a 2D space based upon the closeness of their expression pro_les. Overlay of a minimal spanning tree (MST) identifies the longest continual path linking these cells – uncovering cell lineages. (5) Individual trajectories can be dissected and changes in specific gene expression changes plotted in both a supervised and unsupervised manner (6) The development of algorithms (e.g. StemID, SCENT) has enabled the prediction of cell clusters with high potency, stem-like features. Used in conjunction with pseudotime analysis, these algorithms can infer a starting point of differentiation trajectories, as well as identifying novel stem cells in adult tissues.
Biomimetic Hydrogel Microspheres, supplied by BioMimetic Therapeutics, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/microfluidic+tissue+processor-based/biomimetic+microspheres/10__1039_slash_d0ra07318k-24-95-95
Average 90 stars, based on 1 article reviews
biomimetic hydrogel microspheres - by Bioz Stars, 2026-09
90/100 stars
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human lung diseases  (Tara Biosystems)
90
Tara Biosystems human lung diseases
Transcriptomic profiling of human and embryonic tissues, experimental animal models and patient-derived cell lines via scRNA-seq enables the study of pancreas progenitors. (1) Single-cell suspensions enter high throughput microfluidic systems (e.g. <t>10X</t> Chromium, Drop-Seq) allowing thousands of cells to be processed and sequenced. (2) Cells undergo dimensionality reduction and are clustered based upon expression profiles – represented via UMAP or t-SNE - enabling the identification of novel cell types and investigation of cellular heterogeneity. (3) Following clustering, differential expression analysis reveals changes in gene expression across cell types. (4) Prediction of cell trajectories can be inferred based upon changes in gene expression over a ‘pseudo’ time-course. Cells are ordered in a 2D space based upon the closeness of their expression pro_les. Overlay of a minimal spanning tree (MST) identifies the longest continual path linking these cells – uncovering cell lineages. (5) Individual trajectories can be dissected and changes in specific gene expression changes plotted in both a supervised and unsupervised manner (6) The development of algorithms (e.g. StemID, SCENT) has enabled the prediction of cell clusters with high potency, stem-like features. Used in conjunction with pseudotime analysis, these algorithms can infer a starting point of differentiation trajectories, as well as identifying novel stem cells in adult tissues.
Human Lung Diseases, supplied by Tara Biosystems, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/microfluidic+tissue+processor-based/human+lung+diseases/pm33452532-37-152-150
Average 90 stars, based on 1 article reviews
human lung diseases - by Bioz Stars, 2026-09
90/100 stars
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primovert compact inverted microscope  (Darwin Microfluidics)
99
Darwin Microfluidics primovert compact inverted microscope
Transcriptomic profiling of human and embryonic tissues, experimental animal models and patient-derived cell lines via scRNA-seq enables the study of pancreas progenitors. (1) Single-cell suspensions enter high throughput microfluidic systems (e.g. <t>10X</t> Chromium, Drop-Seq) allowing thousands of cells to be processed and sequenced. (2) Cells undergo dimensionality reduction and are clustered based upon expression profiles – represented via UMAP or t-SNE - enabling the identification of novel cell types and investigation of cellular heterogeneity. (3) Following clustering, differential expression analysis reveals changes in gene expression across cell types. (4) Prediction of cell trajectories can be inferred based upon changes in gene expression over a ‘pseudo’ time-course. Cells are ordered in a 2D space based upon the closeness of their expression pro_les. Overlay of a minimal spanning tree (MST) identifies the longest continual path linking these cells – uncovering cell lineages. (5) Individual trajectories can be dissected and changes in specific gene expression changes plotted in both a supervised and unsupervised manner (6) The development of algorithms (e.g. StemID, SCENT) has enabled the prediction of cell clusters with high potency, stem-like features. Used in conjunction with pseudotime analysis, these algorithms can infer a starting point of differentiation trajectories, as well as identifying novel stem cells in adult tissues.
Primovert Compact Inverted Microscope, supplied by Darwin Microfluidics, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/microfluidic+tissue+processor-based/Primovert+Compact+Inverted+Microscope/custom%40ps-200002174%4030056552
Average 99 stars, based on 1 article reviews
primovert compact inverted microscope - by Bioz Stars, 2026-09
99/100 stars
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ne-1000 syringeone programmable syringe pump  (Darwin Microfluidics)
96
Darwin Microfluidics ne-1000 syringeone programmable syringe pump
Transcriptomic profiling of human and embryonic tissues, experimental animal models and patient-derived cell lines via scRNA-seq enables the study of pancreas progenitors. (1) Single-cell suspensions enter high throughput microfluidic systems (e.g. <t>10X</t> Chromium, Drop-Seq) allowing thousands of cells to be processed and sequenced. (2) Cells undergo dimensionality reduction and are clustered based upon expression profiles – represented via UMAP or t-SNE - enabling the identification of novel cell types and investigation of cellular heterogeneity. (3) Following clustering, differential expression analysis reveals changes in gene expression across cell types. (4) Prediction of cell trajectories can be inferred based upon changes in gene expression over a ‘pseudo’ time-course. Cells are ordered in a 2D space based upon the closeness of their expression pro_les. Overlay of a minimal spanning tree (MST) identifies the longest continual path linking these cells – uncovering cell lineages. (5) Individual trajectories can be dissected and changes in specific gene expression changes plotted in both a supervised and unsupervised manner (6) The development of algorithms (e.g. StemID, SCENT) has enabled the prediction of cell clusters with high potency, stem-like features. Used in conjunction with pseudotime analysis, these algorithms can infer a starting point of differentiation trajectories, as well as identifying novel stem cells in adult tissues.
Ne 1000 Syringeone Programmable Syringe Pump, supplied by Darwin Microfluidics, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/microfluidic+tissue+processor-based/NE-1000+SyringeONE+Programmable+Syringe+Pump/custom%40ne-1000-es%4024656364
Average 96 stars, based on 1 article reviews
ne-1000 syringeone programmable syringe pump - by Bioz Stars, 2026-09
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Image Search Results


Transcriptomic profiling of human and embryonic tissues, experimental animal models and patient-derived cell lines via scRNA-seq enables the study of pancreas progenitors. (1) Single-cell suspensions enter high throughput microfluidic systems (e.g. 10X Chromium, Drop-Seq) allowing thousands of cells to be processed and sequenced. (2) Cells undergo dimensionality reduction and are clustered based upon expression profiles – represented via UMAP or t-SNE - enabling the identification of novel cell types and investigation of cellular heterogeneity. (3) Following clustering, differential expression analysis reveals changes in gene expression across cell types. (4) Prediction of cell trajectories can be inferred based upon changes in gene expression over a ‘pseudo’ time-course. Cells are ordered in a 2D space based upon the closeness of their expression pro_les. Overlay of a minimal spanning tree (MST) identifies the longest continual path linking these cells – uncovering cell lineages. (5) Individual trajectories can be dissected and changes in specific gene expression changes plotted in both a supervised and unsupervised manner (6) The development of algorithms (e.g. StemID, SCENT) has enabled the prediction of cell clusters with high potency, stem-like features. Used in conjunction with pseudotime analysis, these algorithms can infer a starting point of differentiation trajectories, as well as identifying novel stem cells in adult tissues.

Journal: Molecular and Cellular Endocrinology

Article Title: Stem/progenitor cells in normal physiology and disease of the pancreas

doi: 10.1016/j.mce.2021.111459

Figure Lengend Snippet: Transcriptomic profiling of human and embryonic tissues, experimental animal models and patient-derived cell lines via scRNA-seq enables the study of pancreas progenitors. (1) Single-cell suspensions enter high throughput microfluidic systems (e.g. 10X Chromium, Drop-Seq) allowing thousands of cells to be processed and sequenced. (2) Cells undergo dimensionality reduction and are clustered based upon expression profiles – represented via UMAP or t-SNE - enabling the identification of novel cell types and investigation of cellular heterogeneity. (3) Following clustering, differential expression analysis reveals changes in gene expression across cell types. (4) Prediction of cell trajectories can be inferred based upon changes in gene expression over a ‘pseudo’ time-course. Cells are ordered in a 2D space based upon the closeness of their expression pro_les. Overlay of a minimal spanning tree (MST) identifies the longest continual path linking these cells – uncovering cell lineages. (5) Individual trajectories can be dissected and changes in specific gene expression changes plotted in both a supervised and unsupervised manner (6) The development of algorithms (e.g. StemID, SCENT) has enabled the prediction of cell clusters with high potency, stem-like features. Used in conjunction with pseudotime analysis, these algorithms can infer a starting point of differentiation trajectories, as well as identifying novel stem cells in adult tissues.

Article Snippet: Transcriptomic profiling of human and embryonic tissues, experimental animal models and patient-derived cell lines via scRNA-seq enables the study of pancreas progenitors. (1) Single-cell suspensions enter high throughput microfluidic systems (e.g. 10X Chromium, Drop-Seq) allowing thousands of cells to be processed and sequenced. (2) Cells undergo dimensionality reduction and are clustered based upon expression profiles – represented via UMAP or t-SNE - enabling the identification of novel cell types and investigation of cellular heterogeneity. (3) Following clustering, differential expression analysis reveals changes in gene expression across cell types. (4) Prediction of cell trajectories can be inferred based upon changes in gene expression over a ‘pseudo’ time-course.

Techniques: Derivative Assay, High Throughput Screening Assay, Expressing