Analysis of ABIDE dataset: Conventional regression frameworks for optimized algorithmic value. حسب Alexandria M. Jensen (6494957)

الموضوعات:

Distribution of cross correlations in functional connectivity in ABIDE sample. حسب Alexandria M. Jensen (6494957)

الموضوعات:

Multi-scale detection of hierarchical community architecture in structural and functional brain networks حسب Arian Ashourvan (6685232)

"…<div><p>Community detection algorithms have been widely used to study the organization of complex networks like the brain. …"

Examples of between- and within-community Beta distributions. حسب Alexandria M. Jensen (6494957)

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Geometric interpretation and data visualisation equivalent describing the DI algorithmic pipeline. حسب Borjan Milinkovic (21349908)

Workflow of algorithm for whole brain flow simulation. حسب Erlend Hodneland (391541)

<b>Opti2Phase</b>: Python scripts for two-stage focal reducer حسب Morgan Najera (21540776)

"…</li></ul><p dir="ltr">The scripts rely on the following Python packages. Where available, repository links are provided:</p><ol><li><b>NumPy</b>, version 1.22.1</li><li><b>SciPy</b>, version 1.7.3</li><li><b>PyGAD</b>, version 3.0.1 — https://pygad.readthedocs.io/en/latest/#</li><li><b>bees-algorithm</b>, version 1.0.2 — https://pypi.org/project/bees-algorithm</li><li><b>KrakenOS</b>, version 1.0.0.19 — https://github.com/Garchupiter/Kraken-Optical-Simulator</li><li><b>matplotlib</b>, version 3.5.2</li></ol><p dir="ltr">All scripts are modular and organized to reflect the design stages described in the manuscript.…"

Listed python codes of our algorithm with explanations (Python 3.9 recommended). حسب Takayuki Niizato (162226)

Logistic kernel: Power and Type I error for cluster evaluation metric simulations. حسب Alexandria M. Jensen (6494957)

الموضوعات:

ABIDE dataset subject demographics. حسب Alexandria M. Jensen (6494957)

الموضوعات:

Linear kernel: Power and Type I error for cluster evaluation metric simulations. حسب Alexandria M. Jensen (6494957)

الموضوعات:

P-values from analysis of ABIDE dataset for binary outcome of diagnostic group. حسب Alexandria M. Jensen (6494957)

الموضوعات:

Examples of four simulated networks and adjacency matrices. حسب Alexandria M. Jensen (6494957)

الموضوعات:

P-values from analysis of ABIDE dataset for continuous outcome of VIQ. حسب Alexandria M. Jensen (6494957)

الموضوعات:

Reverse engineering information flow using stimulus-encoding and stimulus-transfer estimation algorithms. حسب Gabriel Matías Lorenz (21094672)

Reward function related parameters. حسب Honglei Pang (22693724)

الموضوعات:

Python-based Monte Carlo Simulation Tool حسب Yangfan Jiang (9372782)

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results حسب Se-Hee Jo (20554623)

"…This algorithm conducts a series of procedures: (1) fragmentation of the molecules into functional groups from SMILES, (2) calculation of activity coefficients under predetermined temperature and mole fraction conditions by employing universal quasi-chemical functional group activity coefficient (UNIFAC) model, and (3) regression of NRTL model parameters by employing UNIFAC model simulation results in the differential evolution algorithm (DEA) and Nelder–Mead method (NMM). …"

Consistency of model-derived predictive patterns as a function of sample diversity. حسب Oualid Benkarim (9707986)

Precise spatial delineation of brain cell types in adult mouse brain. حسب Nuray Sogunmez Erdogan (21533872)