Data_Sheet_1_Functional Brain Networks in Mild Cognitive Impairment Based on Resting Electroencephalography Signals.docx 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. …”

Data_Sheet_1_Functional Brain Networks in Mild Cognitive Impairment Based on Resting Electroencephalography Signals.docx 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. …”

Generated blended data using mouse brain cells and human embryonic heart cells, labeled as <i>Mix</i>[<i>a</i>,<i>b</i>,<i>c</i>], indicates the proportion of mouse brain cells fou... by Nuray Sogunmez Erdogan (21533872)

Image_2_Sparse Hierarchical Representation Learning on Functional Brain Networks for Prediction of Autism Severity Levels.TIFF by Hyeokjin Kwon (9314486)

“…<p>Machine learning algorithms have been widely applied in diagnostic tools for autism spectrum disorder (ASD), revealing an altered brain connectivity. …”

Image_3_Sparse Hierarchical Representation Learning on Functional Brain Networks for Prediction of Autism Severity Levels.TIFF by Hyeokjin Kwon (9314486)

“…<p>Machine learning algorithms have been widely applied in diagnostic tools for autism spectrum disorder (ASD), revealing an altered brain connectivity. …”

Image_1_Sparse Hierarchical Representation Learning on Functional Brain Networks for Prediction of Autism Severity Levels.TIFF by Hyeokjin Kwon (9314486)

“…<p>Machine learning algorithms have been widely applied in diagnostic tools for autism spectrum disorder (ASD), revealing an altered brain connectivity. …”

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

PyNoetic’s classification module supports a range of popular and widely used ML classification models with just a single line of function call. by Gursimran Singh (575288)

Subjects:

Image_2_Distinct Brain Dynamic Functional Connectivity Patterns in Schizophrenia Patients With and Without Auditory Verbal Hallucinations.JPEG by Yao Zhang (134381)

“…In this study, 25 Schizophrenia patients with AVHs (AVHs group, 23.2 ± 5.35 years), 52 Schizophrenia patients without AVHs (non-AVHs group, 25.79 ± 5.63 years) and 28 healthy subjects (NC group, 26.14 ± 5.45 years) were enrolled. Dynamic functional connectivity was studied with a sliding-window method and functional connectivity states were then obtained with the k-means clustering algorithm in the three groups. …”

Image_3_Distinct Brain Dynamic Functional Connectivity Patterns in Schizophrenia Patients With and Without Auditory Verbal Hallucinations.JPEG by Yao Zhang (134381)

“…In this study, 25 Schizophrenia patients with AVHs (AVHs group, 23.2 ± 5.35 years), 52 Schizophrenia patients without AVHs (non-AVHs group, 25.79 ± 5.63 years) and 28 healthy subjects (NC group, 26.14 ± 5.45 years) were enrolled. Dynamic functional connectivity was studied with a sliding-window method and functional connectivity states were then obtained with the k-means clustering algorithm in the three groups. …”

Image_1_Distinct Brain Dynamic Functional Connectivity Patterns in Schizophrenia Patients With and Without Auditory Verbal Hallucinations.JPEG by Yao Zhang (134381)

“…In this study, 25 Schizophrenia patients with AVHs (AVHs group, 23.2 ± 5.35 years), 52 Schizophrenia patients without AVHs (non-AVHs group, 25.79 ± 5.63 years) and 28 healthy subjects (NC group, 26.14 ± 5.45 years) were enrolled. Dynamic functional connectivity was studied with a sliding-window method and functional connectivity states were then obtained with the k-means clustering algorithm in the three groups. …”

Resting state functional MRI brain signatures of fast disease progression in amyotrophic lateral sclerosis: a retrospective study by Francesca Trojsi (707124)

“…We aim to investigate brain functional and structural magnetic resonance imaging (MRI) changes in a cohort of ALS patients, examined at diagnosis and clinically monitored over 18 months, in order to early discriminate fast progressors (FPs) from slow progressors (SPs). …”

BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data by Jean-Christophe Lachance (6619307)

“…Despite its importance, no standardized computational platform is currently available to generate species-specific biomass objective functions in a data-driven, unbiased fashion. To fill this gap in the metabolic modeling software ecosystem, we implemented BOFdat, a Python package for the definition of a <b>B</b>iomass <b>O</b>bjective <b>F</b>unction from experimental <b>dat</b>a. …”

IJGIS-code&data.rar by Sancheng Zhu (8801357)

Data_Sheet_1_Sparse Hierarchical Representation Learning on Functional Brain Networks for Prediction of Autism Severity Levels.docx by Hyeokjin Kwon (9314486)

“…<p>Machine learning algorithms have been widely applied in diagnostic tools for autism spectrum disorder (ASD), revealing an altered brain connectivity. …”

Video_1_Sparse Hierarchical Representation Learning on Functional Brain Networks for Prediction of Autism Severity Levels.MP4 by Hyeokjin Kwon (9314486)

“…<p>Machine learning algorithms have been widely applied in diagnostic tools for autism spectrum disorder (ASD), revealing an altered brain connectivity. …”

Functional modules. by Mehrnaz Shoushtarian (6411299)

Python code for a rule-based NLP model for mapping circular economy indicators to SDGs by Zahir Barahmand (18008947)

“…The package includes:</p><ul><li>The complete Python codebase implementing the classification algorithm</li><li>A detailed manual outlining model features, requirements, and usage instructions</li><li>Sample input CSV files and corresponding processed output files to demonstrate functionality</li><li>Keyword dictionaries for all 17 SDGs, distinguishing strong and weak matches</li></ul><p dir="ltr">These materials enable full reproducibility of the study, facilitate adaptation for related research, and offer transparency in the methodological framework.…”

Longitudinal trajectories of functional network development across the birth transition. by Lanxin Ji (20290942)

Discovery of Protein Modifications Using Differential Tandem Mass Spectrometry Proteomics by Paolo Cifani (1575613)

“…Termed SAMPEI for spectral alignment-based modified peptide identification, this open-source algorithm is designed for the discovery of functional protein and peptide signaling modifications, without prior knowledge of their identities. …”