matlab’s in-house functions Search Results


matlab toolboxes  (MathWorks Inc)
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house matlab functions  (MathWorks Inc)
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in house matlab toolbox  (MathWorks Inc)
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matlab r2018b compiler  (MathWorks Inc)
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source matlab signal processing toolbox fieldtrip  (MathWorks Inc)
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bvqx toolbox  (MathWorks Inc)
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squares opls model  (MathWorks Inc)
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A) Experimental procedures overview. Clinical data and peripheral blood were collected preoperatively, and the snap-frozen surgical pancreatic tissue used for LCM of the islets of Langerhans. Blood samples were analyzed for lipidomics, while LCM islets for transcriptomics and proteomics. Omics datasets were individually evaluated in relationship to glycemic status and further integrated with each other using Consensus Orthogonal Partial Least Squares <t>(OPLS)</t> analysis. B) Waffle plot showing the structure of the cohort in terms of glycemic/diabetes categories based on American Diabetes Association criteria. Absolute numbers for each category are given in the legend boxes. C) Boxplots of four major clinical parameters relevant for diabetes diagnosis and management. Statistically significant differences from ND PPP were determined using the Student’s t-test (* p <0.05; ** p <0.01). LCM Laser Capture Microdissection, ND Non-diabetic, IGT Impaired Glucose Tolerance, T3cD Type 3c Diabetes, T2D Type 2 Diabetes.
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matlab computer vision toolbox  (MathWorks Inc)
96
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A) Experimental procedures overview. Clinical data and peripheral blood were collected preoperatively, and the snap-frozen surgical pancreatic tissue used for LCM of the islets of Langerhans. Blood samples were analyzed for lipidomics, while LCM islets for transcriptomics and proteomics. Omics datasets were individually evaluated in relationship to glycemic status and further integrated with each other using Consensus Orthogonal Partial Least Squares <t>(OPLS)</t> analysis. B) Waffle plot showing the structure of the cohort in terms of glycemic/diabetes categories based on American Diabetes Association criteria. Absolute numbers for each category are given in the legend boxes. C) Boxplots of four major clinical parameters relevant for diabetes diagnosis and management. Statistically significant differences from ND PPP were determined using the Student’s t-test (* p <0.05; ** p <0.01). LCM Laser Capture Microdissection, ND Non-diabetic, IGT Impaired Glucose Tolerance, T3cD Type 3c Diabetes, T2D Type 2 Diabetes.
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Image Search Results


A) Experimental procedures overview. Clinical data and peripheral blood were collected preoperatively, and the snap-frozen surgical pancreatic tissue used for LCM of the islets of Langerhans. Blood samples were analyzed for lipidomics, while LCM islets for transcriptomics and proteomics. Omics datasets were individually evaluated in relationship to glycemic status and further integrated with each other using Consensus Orthogonal Partial Least Squares (OPLS) analysis. B) Waffle plot showing the structure of the cohort in terms of glycemic/diabetes categories based on American Diabetes Association criteria. Absolute numbers for each category are given in the legend boxes. C) Boxplots of four major clinical parameters relevant for diabetes diagnosis and management. Statistically significant differences from ND PPP were determined using the Student’s t-test (* p <0.05; ** p <0.01). LCM Laser Capture Microdissection, ND Non-diabetic, IGT Impaired Glucose Tolerance, T3cD Type 3c Diabetes, T2D Type 2 Diabetes.

Journal: bioRxiv

Article Title: Multi-omics profiling of living human pancreatic islet donors reveals heterogeneous beta cell trajectories toward type 2 diabetes

doi: 10.1101/2020.12.05.412338

Figure Lengend Snippet: A) Experimental procedures overview. Clinical data and peripheral blood were collected preoperatively, and the snap-frozen surgical pancreatic tissue used for LCM of the islets of Langerhans. Blood samples were analyzed for lipidomics, while LCM islets for transcriptomics and proteomics. Omics datasets were individually evaluated in relationship to glycemic status and further integrated with each other using Consensus Orthogonal Partial Least Squares (OPLS) analysis. B) Waffle plot showing the structure of the cohort in terms of glycemic/diabetes categories based on American Diabetes Association criteria. Absolute numbers for each category are given in the legend boxes. C) Boxplots of four major clinical parameters relevant for diabetes diagnosis and management. Statistically significant differences from ND PPP were determined using the Student’s t-test (* p <0.05; ** p <0.01). LCM Laser Capture Microdissection, ND Non-diabetic, IGT Impaired Glucose Tolerance, T3cD Type 3c Diabetes, T2D Type 2 Diabetes.

Article Snippet: Consensus Orthogonal Partial Least Squares (OPLS) model was computed with the MATLAB 9 environment with combinations of toolboxes and in-house functions that are available at https://gitlab.unige.ch/Julien.Boccard/consensusopls .

Techniques: Laser Capture Microdissection