Fig 2 - by Anant Shinde (3954662)

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Fig 5 - by Anant Shinde (3954662)

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Data_Sheet_1_Application of Machine Learning and Weighted Gene Co-expression Network Algorithm to Explore the Hub Genes in the Aging Brain.DOCX by Keping Chai (11574214)

Data_Sheet_1_Comparison of Resting-State Functional MRI Methods for Characterizing Brain Dynamics.DOCX by Eric Maltbie (445150)

“…The individual frames can then be clustered to produce temporal groupings commonly referred to as “brain states.” Several recent publications have investigated brain state alterations in clinical populations, typically using a single method for quantifying frame-wise functional connectivity. …”

Video_1_Comparison of Resting-State Functional MRI Methods for Characterizing Brain Dynamics.MP4 by Eric Maltbie (445150)

“…The individual frames can then be clustered to produce temporal groupings commonly referred to as “brain states.” Several recent publications have investigated brain state alterations in clinical populations, typically using a single method for quantifying frame-wise functional connectivity. …”

Table_1_Functional Brain Networks in Mild Cognitive Impairment Based on Resting Electroencephalography Signals.XLSX by Nadia Youssef (11586382)

“…<p>The oscillatory patterns of electroencephalography (EEG), during resting states, are informative and helpful in understanding the functional states of brain network and their contribution to behavioral performances. …”

Table_1_Functional Brain Networks in Mild Cognitive Impairment Based on Resting Electroencephalography Signals.XLSX by Nadia Youssef (11586382)

“…<p>The oscillatory patterns of electroencephalography (EEG), during resting states, are informative and helpful in understanding the functional states of brain network and their contribution to behavioral performances. …”

Identification of genetic markers for cortical areas using a Random Forest classification routine and the Allen Mouse Brain Atlas by Natalie Weed (7345124)

“…<div><p>The mammalian neocortex is subdivided into a series of cortical areas that are functionally and anatomically distinct and are often distinguished in brain sections using histochemical stains and other markers of protein expression. …”

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

Parameters in the neuron-astrocyte model and model training. by Lulu Gong (18707874)

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Learning performance. by Lulu Gong (18707874)

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Fig 3 - by Lulu Gong (18707874)

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Fig 1 - by Lulu Gong (18707874)

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Neuron-astrocyte network motifs and dynamic properties. by Lulu Gong (18707874)

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Performance assessment of Cell2Spatial on real and simulated mouse brain spatial transcriptomics (ST) data. by Huamei Li (8815955)

Presentation_1_Aberrant Whole-Brain Transitions and Dynamics of Spontaneous Network Microstates in Mild Traumatic Brain Injury.zip by Marios Antonakakis (8304126)

“…<p>Dynamic Functional Connectivity (DFC) analysis is a promising approach for the characterization of brain electrophysiological activity. …”

Explained variance ration of the PCA algorithm. by Abeer Aljohani (18497914)

“…<div><p>Chest X-ray image classification plays an important role in medical diagnostics. Machine learning algorithms enhanced the performance of these classification algorithms by introducing advance techniques. …”

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

Data Sheet 1_Simplified two-compartment neuron with calcium dynamics capturing brain-state specific apical-amplification, -isolation and -drive.pdf by Elena Pastorelli (7024235)

“…This work provides the computational community with a two-compartment spiking neuron model that supports the proposed forms of brain-state-specific activity. A machine learning evolutionary algorithm, guided by a set of fitness functions, selected parameters defining neurons that express the desired apical dendritic mechanisms. …”

Main parameters of braking system. by Honglei Pang (22693724)

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