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matlab code 2017b  (MathWorks Inc)


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    MathWorks Inc matlab code 2017b
    Matlab Code 2017b, 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+code+2017b/pm34928427-107-2-4
    Average 90 stars, based on 1 article reviews
    matlab code 2017b - by Bioz Stars, 2026-09
    90/100 stars

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    Article Title: Stimulus-specific and adaptive value representations in the basolateral amygdala in male mice.
    Article Snippet: Statistical analyses and data presentation Statistical analysis was performed with Matlab 2017b and Matlab 2022a (Mathworks).

    Article Title: Stimulus-specific and adaptive value representations in the basolateral amygdala in male mice
    Article Snippet: Statistical analysis was performed with Matlab 2017b and Matlab 2022a (Mathworks).

    Article Title: Decoding basic emotional states through integration of an fNIRS-based brain-computer interface with supervised learning algorithms.
    Article Snippet: The extracted features were 1) maximum, 2) range (i.e., amplitude difference between maximum and minimum signal values), 3) signal to noise ratio, 4) peak time, 5) skewness, 6) kurtosis, 7) variance, 8) median, 9) root mean square, 10) area under the curve and step response characteristics obtained with ‘stepinfo’ function implemented in MATLAB 2017B (The Mathworks Inc., Natick, MA, USA) which included 11) rise time, 12) settling time, 13) settling min, 14) settling max and 15–20) coefficients of a fifth-degree polynomial which was fitted to each channel and stimulus specific truncated time series HbO data.

    Article Title: Interoception vs. Exteroception: Cardiac interoception competes with tactile perception, yet also facilitates self-relevance encoding
    Article Snippet: The task was presented with Matlab 2017b ( ) using the Psychtoolbox , running on a MacBook Air stimulation laptop.

    Article Title: Stimulus-specific and adaptive value representations in the basolateral amygdala in male mice.
    Article Snippet: All analysis of calcium data was performed on deconvolved traces (variable C_dec) extracted through CNMF and performed using Matlab 2017b (Mathworks, code available on Github).

    Article Title: Stimulus-specific and adaptive value representations in the basolateral amygdala in male mice
    Article Snippet: All analysis of calcium data was performed on deconvolved traces (variable C_dec ) extracted through CNMF and performed using Matlab 2017b (Mathworks, code available on Github).

    Article Title: A comprehensive study of template-based frequency detection methods in SSVEP-based brain-computer interfaces.
    Article Snippet: Recently, SSVEP-based brain–computer interfaces (BCIs) have received increasing attention from researchers due to their high signal-to-noise ratios (SNR), high information transfer rates (ITR), and low user training.. Therefore, various methods have been proposed to recognize the frequency of SSVEPs.. This paper reviewed the state-of-the-art frequency detection methods in SSVEP-based BCIs.

    Article Title: Distinct neural bases of subcomponents of the attentional blink
    Article Snippet: Stimulus presentation and data acquisition were programmed with Psychtoolbox ( ) and MATLAB 2017b MathWorks Inc (2017), (Natick, MA.).



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    Gene expression profiling. ( a ) Workflow: from raw dataset to analysis. ( b ) Number of DEGs, up- and down-regulated genes. ( c ) Venn diagram to display the DEGs. ( d ) Venn diagram for enriched pathways for the DEGs (p-value ≤ 0.05). ( e ) Venn diagram for enriched pathways for the DEGs (p-value ≤ 0.001). ( f ) Common genes between different stages and the array chips (U133A and U133B) with their fold changes. ( g ) Mapped network for all the genes in ( f ). For venn diagram plotting, freely available webserver ( http://bioinformatics.psb.ugent.be/webtools/Venn/ ) was used and the heatmaps and bar plot were generated by using MATLAB <t>2017b</t> by using imagesc and plot commands, respectively.
    Matlab 2017b Codes, 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
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    MathWorks Inc matlab code 2017b
    Gene expression profiling. ( a ) Workflow: from raw dataset to analysis. ( b ) Number of DEGs, up- and down-regulated genes. ( c ) Venn diagram to display the DEGs. ( d ) Venn diagram for enriched pathways for the DEGs (p-value ≤ 0.05). ( e ) Venn diagram for enriched pathways for the DEGs (p-value ≤ 0.001). ( f ) Common genes between different stages and the array chips (U133A and U133B) with their fold changes. ( g ) Mapped network for all the genes in ( f ). For venn diagram plotting, freely available webserver ( http://bioinformatics.psb.ugent.be/webtools/Venn/ ) was used and the heatmaps and bar plot were generated by using MATLAB <t>2017b</t> by using imagesc and plot commands, respectively.
    Matlab Code 2017b, 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
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    MathWorks Inc in-house code matlab 2017b
    Gene expression profiling. ( a ) Workflow: from raw dataset to analysis. ( b ) Number of DEGs, up- and down-regulated genes. ( c ) Venn diagram to display the DEGs. ( d ) Venn diagram for enriched pathways for the DEGs (p-value ≤ 0.05). ( e ) Venn diagram for enriched pathways for the DEGs (p-value ≤ 0.001). ( f ) Common genes between different stages and the array chips (U133A and U133B) with their fold changes. ( g ) Mapped network for all the genes in ( f ). For venn diagram plotting, freely available webserver ( http://bioinformatics.psb.ugent.be/webtools/Venn/ ) was used and the heatmaps and bar plot were generated by using MATLAB <t>2017b</t> by using imagesc and plot commands, respectively.
    In House Code Matlab 2017b, 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
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    Gene expression profiling. ( a ) Workflow: from raw dataset to analysis. ( b ) Number of DEGs, up- and down-regulated genes. ( c ) Venn diagram to display the DEGs. ( d ) Venn diagram for enriched pathways for the DEGs (p-value ≤ 0.05). ( e ) Venn diagram for enriched pathways for the DEGs (p-value ≤ 0.001). ( f ) Common genes between different stages and the array chips (U133A and U133B) with their fold changes. ( g ) Mapped network for all the genes in ( f ). For venn diagram plotting, freely available webserver ( http://bioinformatics.psb.ugent.be/webtools/Venn/ ) was used and the heatmaps and bar plot were generated by using MATLAB 2017b by using imagesc and plot commands, respectively.

    Journal: Scientific Reports

    Article Title: Multi-staged gene expression profiling reveals potential genes and the critical pathways in kidney cancer

    doi: 10.1038/s41598-022-11143-6

    Figure Lengend Snippet: Gene expression profiling. ( a ) Workflow: from raw dataset to analysis. ( b ) Number of DEGs, up- and down-regulated genes. ( c ) Venn diagram to display the DEGs. ( d ) Venn diagram for enriched pathways for the DEGs (p-value ≤ 0.05). ( e ) Venn diagram for enriched pathways for the DEGs (p-value ≤ 0.001). ( f ) Common genes between different stages and the array chips (U133A and U133B) with their fold changes. ( g ) Mapped network for all the genes in ( f ). For venn diagram plotting, freely available webserver ( http://bioinformatics.psb.ugent.be/webtools/Venn/ ) was used and the heatmaps and bar plot were generated by using MATLAB 2017b by using imagesc and plot commands, respectively.

    Article Snippet: MATLAB 2017b codes and the command line codes have been used for figure plotting and during analysis.

    Techniques: Expressing, Generated

    Connectivity in the selected networks (where the gene connectivity is not visible), for the top 30 genes matched with those pathways which are enriched for the DEGs list. ( a – f ) Connectivity of the genes in the network for Stage I and II of U133A. These sub-figures were plotted by using MATLAB 2017b by using plot command and afterward dot option was selected and the line was removed.

    Journal: Scientific Reports

    Article Title: Multi-staged gene expression profiling reveals potential genes and the critical pathways in kidney cancer

    doi: 10.1038/s41598-022-11143-6

    Figure Lengend Snippet: Connectivity in the selected networks (where the gene connectivity is not visible), for the top 30 genes matched with those pathways which are enriched for the DEGs list. ( a – f ) Connectivity of the genes in the network for Stage I and II of U133A. These sub-figures were plotted by using MATLAB 2017b by using plot command and afterward dot option was selected and the line was removed.

    Article Snippet: MATLAB 2017b codes and the command line codes have been used for figure plotting and during analysis.

    Techniques: