biolog phenotypic arrays  (Biolog Inc)

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

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

Journal: PLOS Pathogens

Article Title: Exploring the metabolic profile of A . baumannii for antimicrobial development using genome-scale modeling

doi: 10.1371/journal.ppat.1012528

Figure Lengend Snippet: From the Biolog data, only substances mappable to model metabolites were included, while the M9 medium was applied. (a) and (b) The model’s ability to catabolize various carbon and nitrogen sources was assessed using the strain-specific phenotypic data by Farrugia et al . . Grey indicates no growth, and orange indicates growth. Totally, 80 and 48 compounds were tested as sole carbon and nitrogen sources, respectively. Out of these, 69 and 38 phenotypes were recapitulated successfully by i ACB23LX. (c) Confusion matrices of model predictions and Biolog experimental measurements. The overall accuracy of i ACB23LX is 86.3% for the carbon (left matrix) and 79.2% for the nitrogen (right matrix) testings. Orange represents correct predictions, and grey represents wrong predictions.

Article Snippet: We employed the previously published Biolog Phenotypic Array data by Farrugia et al . for A . baumannii ATCC 17978 to validate the functionality of our model [ ].

Techniques: