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biolog phenotypic arrays  (Biolog Inc)

 
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    Biolog Inc biolog phenotypic arrays
    A comparison between carbon utilization in iDR479 model and experimental data indicates 85% concordance (68 out of 80) between the model predictions and the Biolog <t>phenotypic</t> array results. (B) A comparison between AA essentiality results in iDR479 model and experimental data. The model achieved 100% concordance compared with the leave-out experimental results. TP : True positive, the model and the experimental data predict a positive result. TN: True negative, the model and amino acid leave out experiments predict a positive result. FN: False negative, the model predicts a negative result while experimental data predicts a positive result. FP: False positive, the model predicts a positive result while experimental data predicts a negative result.
    Biolog Phenotypic Arrays, supplied by Biolog Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/phenotyping+arrays/bio_rxiv__64898__2026__05__01__720924-31-8-8?v=Biolog+Inc
    Average 86 stars, based on 1 article reviews
    biolog phenotypic arrays - by Bioz Stars, 2026-07
    86/100 stars

    Images

    1) Product Images from "The first digital twin of Enterococcus faecium metabolism reproduces high-throughput phenotyping data"

    Article Title: The first digital twin of Enterococcus faecium metabolism reproduces high-throughput phenotyping data

    Journal: bioRxiv

    doi: 10.64898/2026.05.01.720924

    A comparison between carbon utilization in iDR479 model and experimental data indicates 85% concordance (68 out of 80) between the model predictions and the Biolog phenotypic array results. (B) A comparison between AA essentiality results in iDR479 model and experimental data. The model achieved 100% concordance compared with the leave-out experimental results. TP : True positive, the model and the experimental data predict a positive result. TN: True negative, the model and amino acid leave out experiments predict a positive result. FN: False negative, the model predicts a negative result while experimental data predicts a positive result. FP: False positive, the model predicts a positive result while experimental data predicts a negative result.
    Figure Legend Snippet: A comparison between carbon utilization in iDR479 model and experimental data indicates 85% concordance (68 out of 80) between the model predictions and the Biolog phenotypic array results. (B) A comparison between AA essentiality results in iDR479 model and experimental data. The model achieved 100% concordance compared with the leave-out experimental results. TP : True positive, the model and the experimental data predict a positive result. TN: True negative, the model and amino acid leave out experiments predict a positive result. FN: False negative, the model predicts a negative result while experimental data predicts a positive result. FP: False positive, the model predicts a positive result while experimental data predicts a negative result.

    Techniques Used: Comparison



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    A comparison between carbon utilization in iDR479 model and experimental data indicates 85% concordance (68 out of 80) between the model predictions and the Biolog <t>phenotypic</t> array results. (B) A comparison between AA essentiality results in iDR479 model and experimental data. The model achieved 100% concordance compared with the leave-out experimental results. TP : True positive, the model and the experimental data predict a positive result. TN: True negative, the model and amino acid leave out experiments predict a positive result. FN: False negative, the model predicts a negative result while experimental data predicts a positive result. FP: False positive, the model predicts a positive result while experimental data predicts a negative result.
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    Model validation results. A: comparison of Biolog <t>phenotypic</t> microarray results for U. isabellina CBS167.80 with iUmbe1 model simulations; B: comparison of experimental and computed growth rates of U. isabellina with different carbon sources, A1 - flask cultures data from Chatzifragkou A. et al# , A2 - cultures held in a 3 litre bioreactor from Chatzifragkou A. et al# , B - cultures held in a 3 litre bioreactor from Meeuwse et al# , C - flask cultures data from Fakas S. et al# , D - flask cultures data from Gardeli C. et al# ; C: utilization of model reactions observed in simulations conducted with different carbon sources, D: activity of “Active at least once” reactions set among all 59 simulations with different carbon sources. Red dashed lines separate the 10 % and 90 % activity thresholds, dividing the graph into three groups of near core reactions (violet), carbon source type related reactions (green), carbon-source specific reactions (blue).
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    Model validation results. A: comparison of Biolog <t>phenotypic</t> microarray results for U. isabellina CBS167.80 with iUmbe1 model simulations; B: comparison of experimental and computed growth rates of U. isabellina with different carbon sources, A1 - flask cultures data from Chatzifragkou A. et al# , A2 - cultures held in a 3 litre bioreactor from Chatzifragkou A. et al# , B - cultures held in a 3 litre bioreactor from Meeuwse et al# , C - flask cultures data from Fakas S. et al# , D - flask cultures data from Gardeli C. et al# ; C: utilization of model reactions observed in simulations conducted with different carbon sources, D: activity of “Active at least once” reactions set among all 59 simulations with different carbon sources. Red dashed lines separate the 10 % and 90 % activity thresholds, dividing the graph into three groups of near core reactions (violet), carbon source type related reactions (green), carbon-source specific reactions (blue).
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    Image Search Results


    A comparison between carbon utilization in iDR479 model and experimental data indicates 85% concordance (68 out of 80) between the model predictions and the Biolog phenotypic array results. (B) A comparison between AA essentiality results in iDR479 model and experimental data. The model achieved 100% concordance compared with the leave-out experimental results. TP : True positive, the model and the experimental data predict a positive result. TN: True negative, the model and amino acid leave out experiments predict a positive result. FN: False negative, the model predicts a negative result while experimental data predicts a positive result. FP: False positive, the model predicts a positive result while experimental data predicts a negative result.

    Journal: bioRxiv

    Article Title: The first digital twin of Enterococcus faecium metabolism reproduces high-throughput phenotyping data

    doi: 10.64898/2026.05.01.720924

    Figure Lengend Snippet: A comparison between carbon utilization in iDR479 model and experimental data indicates 85% concordance (68 out of 80) between the model predictions and the Biolog phenotypic array results. (B) A comparison between AA essentiality results in iDR479 model and experimental data. The model achieved 100% concordance compared with the leave-out experimental results. TP : True positive, the model and the experimental data predict a positive result. TN: True negative, the model and amino acid leave out experiments predict a positive result. FN: False negative, the model predicts a negative result while experimental data predicts a positive result. FP: False positive, the model predicts a positive result while experimental data predicts a negative result.

    Article Snippet: We validated the model on experimental data from Biolog phenotypic arrays and amino acid auxotrophy experiments. iDR479 serves as a starting point for future enhancements and further refinements in the metabolic modeling of E. faecium .

    Techniques: Comparison

    Model validation results. A: comparison of Biolog phenotypic microarray results for U. isabellina CBS167.80 with iUmbe1 model simulations; B: comparison of experimental and computed growth rates of U. isabellina with different carbon sources, A1 - flask cultures data from Chatzifragkou A. et al# , A2 - cultures held in a 3 litre bioreactor from Chatzifragkou A. et al# , B - cultures held in a 3 litre bioreactor from Meeuwse et al# , C - flask cultures data from Fakas S. et al# , D - flask cultures data from Gardeli C. et al# ; C: utilization of model reactions observed in simulations conducted with different carbon sources, D: activity of “Active at least once” reactions set among all 59 simulations with different carbon sources. Red dashed lines separate the 10 % and 90 % activity thresholds, dividing the graph into three groups of near core reactions (violet), carbon source type related reactions (green), carbon-source specific reactions (blue).

    Journal: Computational and Structural Biotechnology Journal

    Article Title: Insights into optimization of oleaginous fungi – genome-scale metabolic reconstruction and analysis of Umbelopsis sp. WA50703

    doi: 10.1016/j.csbj.2025.03.049

    Figure Lengend Snippet: Model validation results. A: comparison of Biolog phenotypic microarray results for U. isabellina CBS167.80 with iUmbe1 model simulations; B: comparison of experimental and computed growth rates of U. isabellina with different carbon sources, A1 - flask cultures data from Chatzifragkou A. et al# , A2 - cultures held in a 3 litre bioreactor from Chatzifragkou A. et al# , B - cultures held in a 3 litre bioreactor from Meeuwse et al# , C - flask cultures data from Fakas S. et al# , D - flask cultures data from Gardeli C. et al# ; C: utilization of model reactions observed in simulations conducted with different carbon sources, D: activity of “Active at least once” reactions set among all 59 simulations with different carbon sources. Red dashed lines separate the 10 % and 90 % activity thresholds, dividing the graph into three groups of near core reactions (violet), carbon source type related reactions (green), carbon-source specific reactions (blue).

    Article Snippet: The data included Biolog phenotypic array results run with U. isabellina CBS167.80.

    Techniques: Biomarker Discovery, Comparison, Microarray, Activity Assay