Journal: BMC Bioinformatics

Article Title: Using flux theory in dynamic omics data sets to identify differentially changing signals using DPoP

doi: 10.1186/s12859-024-05938-9

Figure Lengend Snippet: MATLAB App Based GUI DPoP: the distribution of derivatives at a point, as well as the distribution of slopes, is represented in the GUI on the top left. The inputs/user controls are at the bottom left. The list of signals with significantly positive and negative derivatives is in the column in the middle. The column section on the right displays the results of the GO term enrichment analysis applied to the list of significant signals, with respect to the population of signals. Controls are included in the GUI to select the statistical significance, the normalization factor, the GO database file, GO database field identifier, the first and final timepoint of interest in the regression, the first and final time point of interest within the regression, and the threshold for filtering based on noise or number of consecutive non-zero signals

Article Snippet: No MATLAB toolbox or expertise in installation is required since this app can be used with the free browser-based MATLAB Online terminal which automatically handles toolbox/version compatibility.

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Journal: Magnetic Resonance in Medicine

Article Title: CESTsimu: An open‐source GUI for spectral and spatial CEST simulation

doi: 10.1002/mrm.30430

Figure Lengend Snippet: Layout of CESTsimu GUI, which consists of three modules: “Saturation Settings”, “Exchange Settings”, and “Phantom Settings”.

Article Snippet: No additional MATLAB toolbox is required when installing the CESTsimu App.

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Journal: Magnetic Resonance in Medicine

Article Title: CESTsimu: An open‐source GUI for spectral and spatial CEST simulation

doi: 10.1002/mrm.30430

Figure Lengend Snippet: Demonstration of the “Phantom Settings” module in CESTsimu. The simulation results are generated with amide concentrations ranging from 0.1 to 0.5 M. (A) 1D average Z‐spectra for all nine phantoms. (B) “Phantom Experiment Setting” window (pops up by clicking the “Exp. setting” button in the “Phantom Settings” module) to define exchange parameters for each phantom. (C) Grayscale Z‐value images at 3.5 ppm. (D) MTR asym color maps at 3.5 ppm. The red solid line in (A) indicates that the frequency offset for (C) and (D) is 3.5 ppm. (E,F) Randomly generated Δ B 0 map (e) and rB 1 map (F).

Article Snippet: No additional MATLAB toolbox is required when installing the CESTsimu App.

Techniques: Generated

Journal: Magnetic Resonance in Medicine

Article Title: CESTsimu: An open‐source GUI for spectral and spatial CEST simulation

doi: 10.1002/mrm.30430

Figure Lengend Snippet: Simulation results from CESTsimu with various settings are presented as follows: (A) Z‐spectra with T rec values of 0, 0.2, 0.5, 1.0, 1.5, 2.0 s, and infinity (which is realized by checking the “Reset init. mag.” checkbox). (B) Z‐spectra with B 1 values of 0.8 μ T , 1.6 μ T , 2.4 μ T , and 3.0 μ T . (C) Z‐spectra with T sat of 0.5, 1.0, 2.0, and 3.0 s. (D,E) ROI‐averaged Z‐spectra and MTR asym maps (at 2 ppm) with Guan concentrations ranging from 0 to 100 mM in 12.5 mM increments. (F,G) ROI‐averaged Z‐spectra and MTR asym maps (at 2 ppm) with Guan exchange rates ranging from 200 to 1000 Hz in 100 Hz increments.

Article Snippet: No additional MATLAB toolbox is required when installing the CESTsimu App.

Techniques:

Journal: Magnetic Resonance in Medicine

Article Title: CESTsimu: An open‐source GUI for spectral and spatial CEST simulation

doi: 10.1002/mrm.30430

Figure Lengend Snippet: Δ B 0 and rB 1 maps simulated by CESTsimu (A,D) and measured using WASABI (B,E), along with the Bland‐Altman plot comparing B 0 and B 1 values from CESTsimu and WASABI (C,F).

Article Snippet: No additional MATLAB toolbox is required when installing the CESTsimu App.

Techniques:

Journal: Magnetic Resonance in Medicine

Article Title: CESTsimu: An open‐source GUI for spectral and spatial CEST simulation

doi: 10.1002/mrm.30430

Figure Lengend Snippet: Simulation results on BMsim challenge Cases 1–4 obtained by CESTsimu and Pulseq‐CEST. (A) Amide proton transfer (APT) steady‐state preparation. (B,C) APT transient‐state preparation. (D) WASABI preparation.

Article Snippet: No additional MATLAB toolbox is required when installing the CESTsimu App.

Techniques:

Journal: Magnetic Resonance in Medicine

Article Title: CESTsimu: An open‐source GUI for spectral and spatial CEST simulation

doi: 10.1002/mrm.30430

Figure Lengend Snippet: Simulation results on BMsim challenge Cases 5–8 obtained by CESTsimu and Pulseq‐CEST. (A) Single‐shaped pulse APT preparation. (B,C) Pulsed APT preparation. (D) WASABI preparation.

Article Snippet: No additional MATLAB toolbox is required when installing the CESTsimu App.

Techniques: