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guis implemented under matlab 5  (MathWorks Inc)


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    MathWorks Inc guis implemented under matlab 5
    Guis Implemented Under Matlab 5, supplied by MathWorks Inc, 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/matlab+gui+implementation/pm17079102-88-5-8
    Average 90 stars, based on 1 article reviews
    guis implemented under matlab 5 - by Bioz Stars, 2026-10
    90/100 stars

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    Article Title: A MATLAB-based Instrument Control (MIC) package for fluorescence imaging
    Article Snippet: MATLAB provides the ability to create GUIs and therefore MIC allows for both rapid prototyping and for building custom, high-level user interfaces that can be used for production instruments.

    Article Title: DataXflow: Synergizing data-driven modeling with best parameter fit and optimal control – An efficient data analysis for cancer research
    Article Snippet: JimenaE sets up the corresponding scripts with all specific information via GUIs to run the other two components without any specific MATLAB programming skills.

    Article Title: An efficient procedure for prediction of the load-displacement curve of CFDST columns
    Article Snippet: This paper proposes a novel procedure for prediction of both load-displacement curve and load-carrying capacity of concrete-filled double-skin steel tube (CFDST) columns under uniaxial compression by using convolutional neural network (CNN)-based regression and Nelder-Mead methods.. Firstly, hybrid databases collected from experiments in literature and generated from finite element analyses are employed to build the proposed CNNbased model.. The accuracy of the proposed model is described through a comparison between predictive results of the proposed model and unseen data.

    Article Title: Multicore fiber optic imaging reveals that astrocyte calcium activity in the mouse cerebral cortex is modulated by internal motivational state.
    Article Snippet: Once coverslip is cemented, we disinfected and filled cannulas with 3 alternative washes of sterile 0.9% NaCl (Baxter Healthcare) & 70% Ethanol, placed stylet-in-guides at two corners, cement-set the baseplate on skull (Grip Cement, Dentsply International), sealed coverslip corners with tissue adhesive (VetBond, 3M) or UV curable optical adhesive (NOA61, Norland Products), and built layers of cement around guides (Grip Cement, Dentsply International).

    Article Title: Proximal policy optimization-based reinforcement learning approach for DC-DC boost converter control: A comparative evaluation against traditional control techniques
    Article Snippet: Following that, the neural network is built and trained using MATLAB's graphical user interfaces (GUIs) intended exclusively for neural network (NN) applications.

    Article Title: Fast Multidimensional Flow Nuclear Magnetic Resonance at High Field for Real‐Time Reaction Monitoring and Flow Synthesis
    Article Snippet: Her proficiency in developing Python- and MATLAB-based graphical user interfaces (GUIs) has played a key role in enhancing data analysis and automating equipment control for flow chemistry.

    Battery:

    Article Title: Multi-day recordings and adaptive stimulation protocols for in-home collection of deep brain stimulation intracranial recordings.
    Article Snippet: This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record.. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article.. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

    Construct:

    Article Title: Multi-day recordings and adaptive stimulation protocols for in-home collection of deep brain stimulation intracranial recordings.
    Article Snippet: This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record.. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article.. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.



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    The Graphical User Interface (GUI) for the MATLAB implementation of <t>CAMV.</t> The left tree contains a searchable list of protein hits in order of decreasing MASCOT score, each peptide assignment made to that protein, and all possible combinations of PTMs for each scan. The middle panel contains the MS2 scan data with pre-labeled peaks. On the right is a survey of the precursor window of the MS1 scan and a view of any quantitation information associated with the assignment. The peptide ladder at the top summarizes the sequencing information: red for an identified fragment, black for missing. A peak color-coding scheme allows for rapid surveillance of the quality of the match: within tolerance (green), within 1.5x tolerance (magenta), unmatched peak (red), and isotopic peak (yellow). Peptides which are pre-emptively excluded by the software appear in red on the left-hand tree. For these peptides, the reason for preemptive exclusion is displayed at the top left of the MS2 panel in place of the sequence ladder, along with an option to proceed with processing.
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    MathWorks Inc guis implemented under matlab 5
    The Graphical User Interface (GUI) for the MATLAB implementation of <t>CAMV.</t> The left tree contains a searchable list of protein hits in order of decreasing MASCOT score, each peptide assignment made to that protein, and all possible combinations of PTMs for each scan. The middle panel contains the MS2 scan data with pre-labeled peaks. On the right is a survey of the precursor window of the MS1 scan and a view of any quantitation information associated with the assignment. The peptide ladder at the top summarizes the sequencing information: red for an identified fragment, black for missing. A peak color-coding scheme allows for rapid surveillance of the quality of the match: within tolerance (green), within 1.5x tolerance (magenta), unmatched peak (red), and isotopic peak (yellow). Peptides which are pre-emptively excluded by the software appear in red on the left-hand tree. For these peptides, the reason for preemptive exclusion is displayed at the top left of the MS2 panel in place of the sequence ladder, along with an option to proceed with processing.
    Guis Implemented Under Matlab 5, supplied by MathWorks Inc, 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/matlab+gui+implementation/pm17079102-88-5-8
    Average 90 stars, based on 1 article reviews
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    The Graphical User Interface (GUI) for the MATLAB implementation of CAMV. The left tree contains a searchable list of protein hits in order of decreasing MASCOT score, each peptide assignment made to that protein, and all possible combinations of PTMs for each scan. The middle panel contains the MS2 scan data with pre-labeled peaks. On the right is a survey of the precursor window of the MS1 scan and a view of any quantitation information associated with the assignment. The peptide ladder at the top summarizes the sequencing information: red for an identified fragment, black for missing. A peak color-coding scheme allows for rapid surveillance of the quality of the match: within tolerance (green), within 1.5x tolerance (magenta), unmatched peak (red), and isotopic peak (yellow). Peptides which are pre-emptively excluded by the software appear in red on the left-hand tree. For these peptides, the reason for preemptive exclusion is displayed at the top left of the MS2 panel in place of the sequence ladder, along with an option to proceed with processing.

    Journal: Methods (San Diego, Calif.)

    Article Title: Computer Aided Manual Validation of Mass Spectrometry-based Proteomic Data

    doi: 10.1016/j.ymeth.2013.03.004

    Figure Lengend Snippet: The Graphical User Interface (GUI) for the MATLAB implementation of CAMV. The left tree contains a searchable list of protein hits in order of decreasing MASCOT score, each peptide assignment made to that protein, and all possible combinations of PTMs for each scan. The middle panel contains the MS2 scan data with pre-labeled peaks. On the right is a survey of the precursor window of the MS1 scan and a view of any quantitation information associated with the assignment. The peptide ladder at the top summarizes the sequencing information: red for an identified fragment, black for missing. A peak color-coding scheme allows for rapid surveillance of the quality of the match: within tolerance (green), within 1.5x tolerance (magenta), unmatched peak (red), and isotopic peak (yellow). Peptides which are pre-emptively excluded by the software appear in red on the left-hand tree. For these peptides, the reason for preemptive exclusion is displayed at the top left of the MS2 panel in place of the sequence ladder, along with an option to proceed with processing.

    Article Snippet: Once an analysis has been user- verified, publication-ready figures and spreadsheets containing the appropriate quantitative data can be generated from accepted assignments. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window caption a7 The Graphical User Interface (GUI) for the MATLAB implementation of CAMV.

    Techniques: Labeling, Quantitation Assay, Sequencing, Software

    Results of CAMV applied to quantitative tyrosine phosphorylation dataset. (A) All peptide matches following user validation of the dataset. Color code: Agreement between algorithm and user 201/317(green), alternate identification chosen by user 4/317 (yellow), additional assignment included by user 79/317 (blue), and assignment rejected by user 33/317 (red). (B) Distribution of user and CAMV decisions versus MASCOT score. Note that in many cases the user rescued the spectra that were pre-emptively excluded by the software, while in other cases the user rejected the spectral assignment based on the poor quality of the match.

    Journal: Methods (San Diego, Calif.)

    Article Title: Computer Aided Manual Validation of Mass Spectrometry-based Proteomic Data

    doi: 10.1016/j.ymeth.2013.03.004

    Figure Lengend Snippet: Results of CAMV applied to quantitative tyrosine phosphorylation dataset. (A) All peptide matches following user validation of the dataset. Color code: Agreement between algorithm and user 201/317(green), alternate identification chosen by user 4/317 (yellow), additional assignment included by user 79/317 (blue), and assignment rejected by user 33/317 (red). (B) Distribution of user and CAMV decisions versus MASCOT score. Note that in many cases the user rescued the spectra that were pre-emptively excluded by the software, while in other cases the user rejected the spectral assignment based on the poor quality of the match.

    Article Snippet: Once an analysis has been user- verified, publication-ready figures and spreadsheets containing the appropriate quantitative data can be generated from accepted assignments. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window caption a7 The Graphical User Interface (GUI) for the MATLAB implementation of CAMV.

    Techniques: Phospho-proteomics, Biomarker Discovery, Software