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n a melanoma scrna seq data oliveira  (ATCC)
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N A Melanoma Scrna Seq Data Oliveira, supplied by ATCC, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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single cell rna sequencing scrna seq data  (Broad Clinical Labs)
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Analysis of the hub genes expression at <t>single</t> <t>cell</t> level in COVID-19. A UMAP showing the major cell types in COVID-19 ( n = 37) and heathy controls ( n = 15) at single-cell transcriptomes. B Density plot of AUC values. C Boxplot comparing AUC values between COVID-19 and healthy controls
Single Cell Rna Sequencing Scrna Seq Data, supplied by Broad Clinical Labs, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Knockout Screening Validates the Immunosuppressive Roles of Novel Immune Checkpoint Candidates Identified by Their Downregulation in Established Inhibitory IC Knockout Transcriptomic Datasets. (A). We first selected 25 well-established inhibitory immune checkpoints expressed on T cells and screened them across 16 GEO datasets containing knockouts of the top 10 inhibitory immune checkpoints. If the knockout of any of these top 10 checkpoints resulted in a decrease of more than 20% in the expression of other inhibitory checkpoints, indicative of immunosuppressive function. Five checkpoints—CTLA4, KLRG1, LAG3, PD1, and TIGIT—exhibited this key function and were used to refine the criteria for identifying novel inhibitory immune checkpoints. (B). We then screened newly identified 45 Treg- and 106 FOXP3⁺-specific plasma membrane proteins across the GEO knockout datasets of these five checkpoints. Genes that were downregulated at least three out of the five datasets were considered as potential inhibitory candidates. A total of seven such genes were identified (highlighted in grey): Ehd4, Cd200r1, Raph1, Bmpr2, Cd38, Cep55, and Prc1. Of these, the Treg-associated inhibitory group identified CEP55, while the FOXP3⁺ group identified Ehd4, Cd200r1, Raph1, Bmpr2, Cd38, and Prc1. (C). Figure C illustrates the expression patterns of five well-established inhibitory ICs in lymph node T cell subsets using single-cell <t>RNA</t> <t>sequencing</t> <t>(scRNA-seq)</t> data. These ICs including CTLA4, KLRG1, LAG3, PD1, and TIGIT were expressed across CD4⁺ T cells, CD8⁺ T cells, mitotic T cells, tissue-resident T cells, and regulatory T cells (Tregs). Figure D shows comparable expression profiles for seven newly identified inhibitory IC candidates: CEP55, CD38, EHD4, CD200R1, PRC1, RAPH1, and CD86 demonstrating similar distribution across the same T cell subsets. (E) Cross-species expression summary of seven newly identified immune checkpoint receptors in Tregs and conventional T cells.
Cell Rna Sequencing Scrna Seq Data, supplied by Broad Clinical Labs, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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fluidigm c1 scrna seq data  (fluidigm)
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Knockout Screening Validates the Immunosuppressive Roles of Novel Immune Checkpoint Candidates Identified by Their Downregulation in Established Inhibitory IC Knockout Transcriptomic Datasets. (A). We first selected 25 well-established inhibitory immune checkpoints expressed on T cells and screened them across 16 GEO datasets containing knockouts of the top 10 inhibitory immune checkpoints. If the knockout of any of these top 10 checkpoints resulted in a decrease of more than 20% in the expression of other inhibitory checkpoints, indicative of immunosuppressive function. Five checkpoints—CTLA4, KLRG1, LAG3, PD1, and TIGIT—exhibited this key function and were used to refine the criteria for identifying novel inhibitory immune checkpoints. (B). We then screened newly identified 45 Treg- and 106 FOXP3⁺-specific plasma membrane proteins across the GEO knockout datasets of these five checkpoints. Genes that were downregulated at least three out of the five datasets were considered as potential inhibitory candidates. A total of seven such genes were identified (highlighted in grey): Ehd4, Cd200r1, Raph1, Bmpr2, Cd38, Cep55, and Prc1. Of these, the Treg-associated inhibitory group identified CEP55, while the FOXP3⁺ group identified Ehd4, Cd200r1, Raph1, Bmpr2, Cd38, and Prc1. (C). Figure C illustrates the expression patterns of five well-established inhibitory ICs in lymph node T cell subsets using single-cell <t>RNA</t> <t>sequencing</t> <t>(scRNA-seq)</t> data. These ICs including CTLA4, KLRG1, LAG3, PD1, and TIGIT were expressed across CD4⁺ T cells, CD8⁺ T cells, mitotic T cells, tissue-resident T cells, and regulatory T cells (Tregs). Figure D shows comparable expression profiles for seven newly identified inhibitory IC candidates: CEP55, CD38, EHD4, CD200R1, PRC1, RAPH1, and CD86 demonstrating similar distribution across the same T cell subsets. (E) Cross-species expression summary of seven newly identified immune checkpoint receptors in Tregs and conventional T cells.
Fluidigm C1 Scrna Seq Data, supplied by fluidigm, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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c1 scrna seq expression count data  (fluidigm)
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Knockout Screening Validates the Immunosuppressive Roles of Novel Immune Checkpoint Candidates Identified by Their Downregulation in Established Inhibitory IC Knockout Transcriptomic Datasets. (A). We first selected 25 well-established inhibitory immune checkpoints expressed on T cells and screened them across 16 GEO datasets containing knockouts of the top 10 inhibitory immune checkpoints. If the knockout of any of these top 10 checkpoints resulted in a decrease of more than 20% in the expression of other inhibitory checkpoints, indicative of immunosuppressive function. Five checkpoints—CTLA4, KLRG1, LAG3, PD1, and TIGIT—exhibited this key function and were used to refine the criteria for identifying novel inhibitory immune checkpoints. (B). We then screened newly identified 45 Treg- and 106 FOXP3⁺-specific plasma membrane proteins across the GEO knockout datasets of these five checkpoints. Genes that were downregulated at least three out of the five datasets were considered as potential inhibitory candidates. A total of seven such genes were identified (highlighted in grey): Ehd4, Cd200r1, Raph1, Bmpr2, Cd38, Cep55, and Prc1. Of these, the Treg-associated inhibitory group identified CEP55, while the FOXP3⁺ group identified Ehd4, Cd200r1, Raph1, Bmpr2, Cd38, and Prc1. (C). Figure C illustrates the expression patterns of five well-established inhibitory ICs in lymph node T cell subsets using single-cell <t>RNA</t> <t>sequencing</t> <t>(scRNA-seq)</t> data. These ICs including CTLA4, KLRG1, LAG3, PD1, and TIGIT were expressed across CD4⁺ T cells, CD8⁺ T cells, mitotic T cells, tissue-resident T cells, and regulatory T cells (Tregs). Figure D shows comparable expression profiles for seven newly identified inhibitory IC candidates: CEP55, CD38, EHD4, CD200R1, PRC1, RAPH1, and CD86 demonstrating similar distribution across the same T cell subsets. (E) Cross-species expression summary of seven newly identified immune checkpoint receptors in Tregs and conventional T cells.
C1 Scrna Seq Expression Count Data, supplied by fluidigm, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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data murine scrna seq data  (ATCC)
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Knockout Screening Validates the Immunosuppressive Roles of Novel Immune Checkpoint Candidates Identified by Their Downregulation in Established Inhibitory IC Knockout Transcriptomic Datasets. (A). We first selected 25 well-established inhibitory immune checkpoints expressed on T cells and screened them across 16 GEO datasets containing knockouts of the top 10 inhibitory immune checkpoints. If the knockout of any of these top 10 checkpoints resulted in a decrease of more than 20% in the expression of other inhibitory checkpoints, indicative of immunosuppressive function. Five checkpoints—CTLA4, KLRG1, LAG3, PD1, and TIGIT—exhibited this key function and were used to refine the criteria for identifying novel inhibitory immune checkpoints. (B). We then screened newly identified 45 Treg- and 106 FOXP3⁺-specific plasma membrane proteins across the GEO knockout datasets of these five checkpoints. Genes that were downregulated at least three out of the five datasets were considered as potential inhibitory candidates. A total of seven such genes were identified (highlighted in grey): Ehd4, Cd200r1, Raph1, Bmpr2, Cd38, Cep55, and Prc1. Of these, the Treg-associated inhibitory group identified CEP55, while the FOXP3⁺ group identified Ehd4, Cd200r1, Raph1, Bmpr2, Cd38, and Prc1. (C). Figure C illustrates the expression patterns of five well-established inhibitory ICs in lymph node T cell subsets using single-cell <t>RNA</t> <t>sequencing</t> <t>(scRNA-seq)</t> data. These ICs including CTLA4, KLRG1, LAG3, PD1, and TIGIT were expressed across CD4⁺ T cells, CD8⁺ T cells, mitotic T cells, tissue-resident T cells, and regulatory T cells (Tregs). Figure D shows comparable expression profiles for seven newly identified inhibitory IC candidates: CEP55, CD38, EHD4, CD200R1, PRC1, RAPH1, and CD86 demonstrating similar distribution across the same T cell subsets. (E) Cross-species expression summary of seven newly identified immune checkpoint receptors in Tregs and conventional T cells.
Data Murine Scrna Seq Data, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Knockout Screening Validates the Immunosuppressive Roles of Novel Immune Checkpoint Candidates Identified by Their Downregulation in Established Inhibitory IC Knockout Transcriptomic Datasets. (A). We first selected 25 well-established inhibitory immune checkpoints expressed on T cells and screened them across 16 GEO datasets containing knockouts of the top 10 inhibitory immune checkpoints. If the knockout of any of these top 10 checkpoints resulted in a decrease of more than 20% in the expression of other inhibitory checkpoints, indicative of immunosuppressive function. Five checkpoints—CTLA4, KLRG1, LAG3, PD1, and TIGIT—exhibited this key function and were used to refine the criteria for identifying novel inhibitory immune checkpoints. (B). We then screened newly identified 45 Treg- and 106 FOXP3⁺-specific plasma membrane proteins across the GEO knockout datasets of these five checkpoints. Genes that were downregulated at least three out of the five datasets were considered as potential inhibitory candidates. A total of seven such genes were identified (highlighted in grey): Ehd4, Cd200r1, Raph1, Bmpr2, Cd38, Cep55, and Prc1. Of these, the Treg-associated inhibitory group identified CEP55, while the FOXP3⁺ group identified Ehd4, Cd200r1, Raph1, Bmpr2, Cd38, and Prc1. (C). Figure C illustrates the expression patterns of five well-established inhibitory ICs in lymph node T cell subsets using single-cell <t>RNA</t> <t>sequencing</t> <t>(scRNA-seq)</t> data. These ICs including CTLA4, KLRG1, LAG3, PD1, and TIGIT were expressed across CD4⁺ T cells, CD8⁺ T cells, mitotic T cells, tissue-resident T cells, and regulatory T cells (Tregs). Figure D shows comparable expression profiles for seven newly identified inhibitory IC candidates: CEP55, CD38, EHD4, CD200R1, PRC1, RAPH1, and CD86 demonstrating similar distribution across the same T cell subsets. (E) Cross-species expression summary of seven newly identified immune checkpoint receptors in Tregs and conventional T cells.
Gse294854 Murine Scrna Seq Data, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Analysis of the hub genes expression at single cell level in COVID-19. A UMAP showing the major cell types in COVID-19 ( n = 37) and heathy controls ( n = 15) at single-cell transcriptomes. B Density plot of AUC values. C Boxplot comparing AUC values between COVID-19 and healthy controls

Journal: Mammalian Genome

Article Title: Exploration of shared gene signatures and molecular mechanisms between psoriasis and COVID-19: evidence from transcriptome data

doi: 10.1007/s00335-026-10194-8

Figure Lengend Snippet: Analysis of the hub genes expression at single cell level in COVID-19. A UMAP showing the major cell types in COVID-19 ( n = 37) and heathy controls ( n = 15) at single-cell transcriptomes. B Density plot of AUC values. C Boxplot comparing AUC values between COVID-19 and healthy controls

Article Snippet: Additionally, single-cell RNA sequencing (scRNA-seq) data of COVID-19 samples were obtained from the Broad Institute Single Cell Portal ( https://singlecell.broadinstitute.org/single_cell/study/SCP1289/ ).

Techniques: Expressing

Analysis of the hub genes expression at single cell level in psoriasis. A UMAP showing major cell types and clusters in psoriasis patients ( n = 3) and healthy controls ( n = 3). B Density plot of AUC values. C Boxplot comparing AUC values between psoriasis and healthy controls

Journal: Mammalian Genome

Article Title: Exploration of shared gene signatures and molecular mechanisms between psoriasis and COVID-19: evidence from transcriptome data

doi: 10.1007/s00335-026-10194-8

Figure Lengend Snippet: Analysis of the hub genes expression at single cell level in psoriasis. A UMAP showing major cell types and clusters in psoriasis patients ( n = 3) and healthy controls ( n = 3). B Density plot of AUC values. C Boxplot comparing AUC values between psoriasis and healthy controls

Article Snippet: Additionally, single-cell RNA sequencing (scRNA-seq) data of COVID-19 samples were obtained from the Broad Institute Single Cell Portal ( https://singlecell.broadinstitute.org/single_cell/study/SCP1289/ ).

Techniques: Expressing

Knockout Screening Validates the Immunosuppressive Roles of Novel Immune Checkpoint Candidates Identified by Their Downregulation in Established Inhibitory IC Knockout Transcriptomic Datasets. (A). We first selected 25 well-established inhibitory immune checkpoints expressed on T cells and screened them across 16 GEO datasets containing knockouts of the top 10 inhibitory immune checkpoints. If the knockout of any of these top 10 checkpoints resulted in a decrease of more than 20% in the expression of other inhibitory checkpoints, indicative of immunosuppressive function. Five checkpoints—CTLA4, KLRG1, LAG3, PD1, and TIGIT—exhibited this key function and were used to refine the criteria for identifying novel inhibitory immune checkpoints. (B). We then screened newly identified 45 Treg- and 106 FOXP3⁺-specific plasma membrane proteins across the GEO knockout datasets of these five checkpoints. Genes that were downregulated at least three out of the five datasets were considered as potential inhibitory candidates. A total of seven such genes were identified (highlighted in grey): Ehd4, Cd200r1, Raph1, Bmpr2, Cd38, Cep55, and Prc1. Of these, the Treg-associated inhibitory group identified CEP55, while the FOXP3⁺ group identified Ehd4, Cd200r1, Raph1, Bmpr2, Cd38, and Prc1. (C). Figure C illustrates the expression patterns of five well-established inhibitory ICs in lymph node T cell subsets using single-cell RNA sequencing (scRNA-seq) data. These ICs including CTLA4, KLRG1, LAG3, PD1, and TIGIT were expressed across CD4⁺ T cells, CD8⁺ T cells, mitotic T cells, tissue-resident T cells, and regulatory T cells (Tregs). Figure D shows comparable expression profiles for seven newly identified inhibitory IC candidates: CEP55, CD38, EHD4, CD200R1, PRC1, RAPH1, and CD86 demonstrating similar distribution across the same T cell subsets. (E) Cross-species expression summary of seven newly identified immune checkpoint receptors in Tregs and conventional T cells.

Journal: Journal of Cancer

Article Title: Discovery of Seven ROS-Sensitive Immune Checkpoints and 46 Ligands Mediating Immune Suppression Through T cell-APC Networks

doi: 10.7150/jca.128083

Figure Lengend Snippet: Knockout Screening Validates the Immunosuppressive Roles of Novel Immune Checkpoint Candidates Identified by Their Downregulation in Established Inhibitory IC Knockout Transcriptomic Datasets. (A). We first selected 25 well-established inhibitory immune checkpoints expressed on T cells and screened them across 16 GEO datasets containing knockouts of the top 10 inhibitory immune checkpoints. If the knockout of any of these top 10 checkpoints resulted in a decrease of more than 20% in the expression of other inhibitory checkpoints, indicative of immunosuppressive function. Five checkpoints—CTLA4, KLRG1, LAG3, PD1, and TIGIT—exhibited this key function and were used to refine the criteria for identifying novel inhibitory immune checkpoints. (B). We then screened newly identified 45 Treg- and 106 FOXP3⁺-specific plasma membrane proteins across the GEO knockout datasets of these five checkpoints. Genes that were downregulated at least three out of the five datasets were considered as potential inhibitory candidates. A total of seven such genes were identified (highlighted in grey): Ehd4, Cd200r1, Raph1, Bmpr2, Cd38, Cep55, and Prc1. Of these, the Treg-associated inhibitory group identified CEP55, while the FOXP3⁺ group identified Ehd4, Cd200r1, Raph1, Bmpr2, Cd38, and Prc1. (C). Figure C illustrates the expression patterns of five well-established inhibitory ICs in lymph node T cell subsets using single-cell RNA sequencing (scRNA-seq) data. These ICs including CTLA4, KLRG1, LAG3, PD1, and TIGIT were expressed across CD4⁺ T cells, CD8⁺ T cells, mitotic T cells, tissue-resident T cells, and regulatory T cells (Tregs). Figure D shows comparable expression profiles for seven newly identified inhibitory IC candidates: CEP55, CD38, EHD4, CD200R1, PRC1, RAPH1, and CD86 demonstrating similar distribution across the same T cell subsets. (E) Cross-species expression summary of seven newly identified immune checkpoint receptors in Tregs and conventional T cells.

Article Snippet: To examine this hypothesis, we searched for single cell RNA-sequencing (scRNA-Seq) data at MIT-Broad Institute Single Cell Portal database.

Techniques: Knock-Out, Expressing, Clinical Proteomics, Membrane, RNA Sequencing