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global pattern recognition software lonza gpr 2.0  (Lonza)


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    Lonza global pattern recognition software lonza gpr 2.0
    Global Pattern Recognition Software Lonza Gpr 2.0, supplied by Lonza, 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/global+pattern+recognition+software/global+pattern+recognition+analytical+software/pmc03325141-110-7-11
    Average 90 stars, based on 1 article reviews
    global pattern recognition software lonza gpr 2.0 - by Bioz Stars, 2026-09
    90/100 stars

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    Related Articles

    Software:

    Article Title: T-cell factor 4 functions as a tumor suppressor whose disruption modulates colon cell proliferation and tumorigenesis
    Article Snippet: QPCR was conducted using either 96-well or 384-well StellARrays (Bar Harbor Biotechnology), including the Mouse Wnt Signaling and Targets of Wnt Signaling arrays, according to the manufacturer's instructions. .. Data were analyzed by Bar Harbor Biotechnology using Global Pattern Recognition software (Lonza) as previously published ( 36 ). ..

    Article Title: T-cell factor 4 functions as a tumor suppressor whose disruption modulates colon cell proliferation and tumorigenesis.
    Article Snippet: QPCR was conducted using either 96-well or 384-well StellARrays (Bar Harbor Biotechnology), including the Mouse Wnt Signaling and Targets of Wnt Signaling arrays, according to the manufacturer’s instructions. .. Data were analyzed by Bar Harbor Biotechnology using Global Pattern Recognition software (Lonza) as previously published (36). ..

    Article Title: Effects of Auraptene on IGF-1 Stimulated Cell Cycle Progression in the Human Breast Cancer Cell Line, MCF-7
    Article Snippet: .. The results from qRT-PCR array studies were analyzed with the Global Pattern Recognition Software available on Lonza's website ( http://array.lonza.com/stellarrays/ ), P < 0.05. ..

    Quantitative RT-PCR:

    Article Title: Effects of Auraptene on IGF-1 Stimulated Cell Cycle Progression in the Human Breast Cancer Cell Line, MCF-7
    Article Snippet: .. The results from qRT-PCR array studies were analyzed with the Global Pattern Recognition Software available on Lonza's website ( http://array.lonza.com/stellarrays/ ), P < 0.05. ..



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    ( a – d ) CD11c dnR and wild type mice were injected ( i.p. ) twice a day with BrdU for 3 days. On day 3, mice were sacrificed and frequency of cycling cells was determined in the bone marrow. ( a – b ) FACS plots show the distribution of BrdU staining among total mNK cells ( a ) and gated mNK cells at stages D, E, and F ( b ). ( c ) Graph shows the frequency of cycling cells in pNK, iNK, and mNK cells from CD11c dnR (black circle) versus wild type (white circle) mice. ( d ) Graph shows the frequency of cycling cells in mNK cells at stages D, E, and F from CD11c dnR (black circle) versus wild type (white circle) mice. Data in a , d are representative of three independent experiments with n = 2 mice per experiment and results in c , d show all 6 individual mice. ( e – f ) mNK cells at stages D, E, and F were sorted from the bone marrow. mRNA was isolated and cDNA was subjected to pathway-specific qPCR for analysis of cell cycle genes ( e ) or SYBR Green qPCR for analysis of transcription factors T-bet, GATA-3, and IRF-2 ( f ). Data were analyzed using <t>Global</t> <t>Pattern</t> <t>Recognition</t> <t>analytical</t> <t>software</t> ( e ) or 2-33C3 method ( f ) and results were expressed as fold of change in CD11c dnR versus wild type samples. Data in e , f are representative of three independent cell sorting with samples pooled from n = 12 CD11c dnR and 25 WT mice.
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    ( a – d ) CD11c dnR and wild type mice were injected ( i.p. ) twice a day with BrdU for 3 days. On day 3, mice were sacrificed and frequency of cycling cells was determined in the bone marrow. ( a – b ) FACS plots show the distribution of BrdU staining among total mNK cells ( a ) and gated mNK cells at stages D, E, and F ( b ). ( c ) Graph shows the frequency of cycling cells in pNK, iNK, and mNK cells from CD11c dnR (black circle) versus wild type (white circle) mice. ( d ) Graph shows the frequency of cycling cells in mNK cells at stages D, E, and F from CD11c dnR (black circle) versus wild type (white circle) mice. Data in a , d are representative of three independent experiments with n = 2 mice per experiment and results in c , d show all 6 individual mice. ( e – f ) mNK cells at stages D, E, and F were sorted from the bone marrow. mRNA was isolated and cDNA was subjected to pathway-specific qPCR for analysis of cell cycle genes ( e ) or SYBR Green qPCR for analysis of transcription factors T-bet, GATA-3, and IRF-2 ( f ). Data were analyzed using <t>Global</t> <t>Pattern</t> <t>Recognition</t> <t>analytical</t> <t>software</t> ( e ) or 2-33C3 method ( f ) and results were expressed as fold of change in CD11c dnR versus wild type samples. Data in e , f are representative of three independent cell sorting with samples pooled from n = 12 CD11c dnR and 25 WT mice.
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    ( a – d ) CD11c dnR and wild type mice were injected ( i.p. ) twice a day with BrdU for 3 days. On day 3, mice were sacrificed and frequency of cycling cells was determined in the bone marrow. ( a – b ) FACS plots show the distribution of BrdU staining among total mNK cells ( a ) and gated mNK cells at stages D, E, and F ( b ). ( c ) Graph shows the frequency of cycling cells in pNK, iNK, and mNK cells from CD11c dnR (black circle) versus wild type (white circle) mice. ( d ) Graph shows the frequency of cycling cells in mNK cells at stages D, E, and F from CD11c dnR (black circle) versus wild type (white circle) mice. Data in a , d are representative of three independent experiments with n = 2 mice per experiment and results in c , d show all 6 individual mice. ( e – f ) mNK cells at stages D, E, and F were sorted from the bone marrow. mRNA was isolated and cDNA was subjected to pathway-specific qPCR for analysis of cell cycle genes ( e ) or SYBR Green qPCR for analysis of transcription factors T-bet, GATA-3, and IRF-2 ( f ). Data were analyzed using <t>Global</t> <t>Pattern</t> <t>Recognition</t> <t>analytical</t> <t>software</t> ( e ) or 2-33C3 method ( f ) and results were expressed as fold of change in CD11c dnR versus wild type samples. Data in e , f are representative of three independent cell sorting with samples pooled from n = 12 CD11c dnR and 25 WT mice.
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    ( a – d ) CD11c dnR and wild type mice were injected ( i.p. ) twice a day with BrdU for 3 days. On day 3, mice were sacrificed and frequency of cycling cells was determined in the bone marrow. ( a – b ) FACS plots show the distribution of BrdU staining among total mNK cells ( a ) and gated mNK cells at stages D, E, and F ( b ). ( c ) Graph shows the frequency of cycling cells in pNK, iNK, and mNK cells from CD11c dnR (black circle) versus wild type (white circle) mice. ( d ) Graph shows the frequency of cycling cells in mNK cells at stages D, E, and F from CD11c dnR (black circle) versus wild type (white circle) mice. Data in a , d are representative of three independent experiments with n = 2 mice per experiment and results in c , d show all 6 individual mice. ( e – f ) mNK cells at stages D, E, and F were sorted from the bone marrow. mRNA was isolated and cDNA was subjected to pathway-specific qPCR for analysis of cell cycle genes ( e ) or SYBR Green qPCR for analysis of transcription factors T-bet, GATA-3, and IRF-2 ( f ). Data were analyzed using Global Pattern Recognition analytical software ( e ) or 2-33C3 method ( f ) and results were expressed as fold of change in CD11c dnR versus wild type samples. Data in e , f are representative of three independent cell sorting with samples pooled from n = 12 CD11c dnR and 25 WT mice.

    Journal: Nature immunology

    Article Title: TGF-β is responsible for NK cell immaturity during ontogeny and increased susceptibility to infection during mouse infancy

    doi: 10.1038/ni.2388

    Figure Lengend Snippet: ( a – d ) CD11c dnR and wild type mice were injected ( i.p. ) twice a day with BrdU for 3 days. On day 3, mice were sacrificed and frequency of cycling cells was determined in the bone marrow. ( a – b ) FACS plots show the distribution of BrdU staining among total mNK cells ( a ) and gated mNK cells at stages D, E, and F ( b ). ( c ) Graph shows the frequency of cycling cells in pNK, iNK, and mNK cells from CD11c dnR (black circle) versus wild type (white circle) mice. ( d ) Graph shows the frequency of cycling cells in mNK cells at stages D, E, and F from CD11c dnR (black circle) versus wild type (white circle) mice. Data in a , d are representative of three independent experiments with n = 2 mice per experiment and results in c , d show all 6 individual mice. ( e – f ) mNK cells at stages D, E, and F were sorted from the bone marrow. mRNA was isolated and cDNA was subjected to pathway-specific qPCR for analysis of cell cycle genes ( e ) or SYBR Green qPCR for analysis of transcription factors T-bet, GATA-3, and IRF-2 ( f ). Data were analyzed using Global Pattern Recognition analytical software ( e ) or 2-33C3 method ( f ) and results were expressed as fold of change in CD11c dnR versus wild type samples. Data in e , f are representative of three independent cell sorting with samples pooled from n = 12 CD11c dnR and 25 WT mice.

    Article Snippet: For cell cycle genes, we used a customized cell cycle qPCR array according to the manufacturer’s instructions (Lonza), and data were analyzed using Global Pattern Recognition analytical software (Lonza).

    Techniques: Injection, BrdU Staining, Isolation, SYBR Green Assay, Software, FACS