Data_Sheet_1_A Comprehensive Analysis of Multilayer Community Detection Algorithms for Application to EEG-Based Brain Networks.docx by Maria Grazia Puxeddu (10211162)

“…Finally, as a proof of concept, we show an application of the algorithms to real functional brain networks derived from EEG signals collected at rest with closed and open eyes. …”

Modular architecture design of PyNoetic showing all its constituent functions. by Gursimran Singh (575288)

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Network propagation improves the correlation between mRNA and protein levels of ageing tissues (brain and liver) and PCa samples. by Konstantina Charmpi (9901053)

Adaptive H-REMD simulation algorithm. by Danial Pourjafar-Dehkordi (7165523)

The workflow used to analyze imbalanced and balanced sequences. by Solomon Shiferaw Beyene (9143178)

Performances of Naïve Bayes (NB), Multilayer Perceptron (MLP), Random Forest (RF), Gradient Boosting (GB), Support Vector Machine (SVM) and K- Nearest Neighbors (KNN). by Solomon Shiferaw Beyene (9143178)

Accuracy, sensitivity, specificity and F-score. by Solomon Shiferaw Beyene (9143178)

The figures showed a comparison of the balanced and imbalanced sequences and performance of classifiers. by Solomon Shiferaw Beyene (9143178)

Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. by Gursimran Singh (575288)

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Estimation accuracy across different structural and functional components of the BVEP model. by Meysam Hashemi (4114738)

“…<p>(<b>A</b>) Excitability values used for simulation () versus the estimated values () for a selected brain region (node number 6). As the node dynamics are varied by changing the excitability parameter (functional component), the model inversion by NUTS algorithm demonstrates an accurate and robust estimation by recovering the ground truth. …”

Image_1_Test-retest reliability of modular-relevant analysis in brain functional network.PDF by Xuyun Wen (414454)

“…Considering the repeatability of network partition depends heavily on network size and module detection algorithm, we constructed three types of brain functional networks for each subject by using a set of coarse-to-fine brain atlases and adopted four methods for single-subject module detection and twelve methods for group-level module detection.…”

Data_Sheet_1_Abnormal Brain Functional Network Dynamics in Acute CO Poisoning.docx by Hongyi Zheng (816158)

“…</p><p>Methods: Combining the sliding window method and k-means algorithm, we identified four recurrent dynamic functional cognitive impairment states from resting-state functional magnetic resonance imaging data from 29 patients in the acute phase of carbon monoxide poisoning and 29 healthy controls. …”

Analyses of Immune microenvironment and functions between m7G clusters. by Jiangli Zhao (2308330)

Spatial characterization and cell-type-specific genes in mouse brain tissue. by Huamei Li (8815955)

A comparison between the static Python-based visualizations of the p65 activity in activated fibroblasts and the dynamic, HTML-based visualizations that use these same reduction me... by Hector Torres (11708207)

Explained variance as a function of number of inner dimensions, <i>Q</i>. by Kai J. Miller (8846117)

Overview of functionality supported by PyNoetic and its various modules, including the live analysis and programmable flowchart. by Gursimran Singh (575288)

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Cost functions implemented in Neuroptimus. by Máté Mohácsi (20469514)

Fig 1 - by Anant Shinde (3954662)

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The top 2 ROI pairs contributing towards the classification of multi-electrode stimulation. by Anant Shinde (3954662)

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