Table_5_Therapeutic Target Analysis and Molecular Mechanism of Melatonin - Treated Leptin Resistance Induced Obesity: A Systematic Study of Network Pharmacology.xlsx حسب Vennila Suriyagandhi (22061534)

"…The top 10 pathways interacted with the common 33 genes and created two functional modules. Using Cytoscape network analysis, the top ten hub genes (TP53, AKT1, MAPK3, PTGS2, TNF, IL6, MAPK1, ERBB2, IL1B, MTOR) were identified by the MCC algorithm of the CytoHubba plugin. …"

Table_1_Therapeutic Target Analysis and Molecular Mechanism of Melatonin - Treated Leptin Resistance Induced Obesity: A Systematic Study of Network Pharmacology.xlsx حسب Vennila Suriyagandhi (22061534)

"…The top 10 pathways interacted with the common 33 genes and created two functional modules. Using Cytoscape network analysis, the top ten hub genes (TP53, AKT1, MAPK3, PTGS2, TNF, IL6, MAPK1, ERBB2, IL1B, MTOR) were identified by the MCC algorithm of the CytoHubba plugin. …"

Table_2_Therapeutic Target Analysis and Molecular Mechanism of Melatonin - Treated Leptin Resistance Induced Obesity: A Systematic Study of Network Pharmacology.xlsx حسب Vennila Suriyagandhi (22061534)

"…The top 10 pathways interacted with the common 33 genes and created two functional modules. Using Cytoscape network analysis, the top ten hub genes (TP53, AKT1, MAPK3, PTGS2, TNF, IL6, MAPK1, ERBB2, IL1B, MTOR) were identified by the MCC algorithm of the CytoHubba plugin. …"

Table_3_Therapeutic Target Analysis and Molecular Mechanism of Melatonin - Treated Leptin Resistance Induced Obesity: A Systematic Study of Network Pharmacology.xlsx حسب Vennila Suriyagandhi (22061534)

"…The top 10 pathways interacted with the common 33 genes and created two functional modules. Using Cytoscape network analysis, the top ten hub genes (TP53, AKT1, MAPK3, PTGS2, TNF, IL6, MAPK1, ERBB2, IL1B, MTOR) were identified by the MCC algorithm of the CytoHubba plugin. …"

Table_5_Therapeutic Target Analysis and Molecular Mechanism of Melatonin - Treated Leptin Resistance Induced Obesity: A Systematic Study of Network Pharmacology.xlsx حسب Vennila Suriyagandhi (22061534)

"…The top 10 pathways interacted with the common 33 genes and created two functional modules. Using Cytoscape network analysis, the top ten hub genes (TP53, AKT1, MAPK3, PTGS2, TNF, IL6, MAPK1, ERBB2, IL1B, MTOR) were identified by the MCC algorithm of the CytoHubba plugin. …"

DataSheet_1_Therapeutic Target Analysis and Molecular Mechanism of Melatonin - Treated Leptin Resistance Induced Obesity: A Systematic Study of Network Pharmacology.docx حسب Vennila Suriyagandhi (22061534)

"…The top 10 pathways interacted with the common 33 genes and created two functional modules. Using Cytoscape network analysis, the top ten hub genes (TP53, AKT1, MAPK3, PTGS2, TNF, IL6, MAPK1, ERBB2, IL1B, MTOR) were identified by the MCC algorithm of the CytoHubba plugin. …"

NanoDB: Research Activity Data Management System حسب Lorenci Gjurgjaj (19702207)

"…Cross-Platform Compatibility: Works on Windows, macOS, and Linux. In a Python environment or as an executable. Ease of Implementation: Using the flexibility of the Python framework all the data setup and algorithm can me modified and new functions can be easily added. …"

Code and data for evaluating oil spill amount from text-form incident information حسب Yiming Liu (18823387)

"…These are separately stored in the folders “description” and “posts”.</p><h2>Algorithms for Evaluating Release Amount (RA)</h2><p dir="ltr">The algorithms are split into the following three notebooks based on their functions:</p><ol><li><b>"1_RA_extraction.ipynb"</b>:</li><li><ul><li>Identifies oil spill-related incidents from raw incident data.…"

Data Sheet 1_Machine learning models integrating intracranial artery calcification to predict outcomes of mechanical thrombectomy.pdf حسب Guangzong Li (16696443)

"…Eleven ML algorithms were trained and validated using Python, and external validation and performance evaluations were conducted. …"

Brain-in-the-Loop Learning for Intelligent Vehicle Decision-Making حسب Xiaofei Zhang (16483224)

"…In this paper, we utilize functional near-infrared spectroscopy (fNIRS) signals as real-time human risk-perception feedback to establish a brain-in-the-loop (BiTL) trained artificial intelligence algorithm for decision-making. …"

Edge-disjoint spanning trees in the Möbius cube حسب Xiaorui Li (748417)

"…EDSTs in a network can facilitate many network functionalities such as improving the rate of data broadcasting, secure message distribution, fault-tolerant broadcasting, etc., and have inspired many researchers’ interest. …"

Mechanomics Code - JVT حسب Carlo Vittorio Cannistraci (5854046)

"…The functions were tested respectively in: MATLAB 2018a or youger, Python 3.9.4, R 4.0.3.…"

Transcription factor of Key regulator genes. حسب Kankana Bhattacharjee (20623639)

"…Our analysis revealed 33 key regulators were predominantly enriched in neuroactive ligand-receptor interaction, Cell adhesion molecules, Leukocyte transendothelial migration pathways; positive regulation of cell proliferation, positive regulation of protein kinase B signaling biological functions; G-protein beta-subunit binding, receptor binding molecular functions etc. …"

Gene-drug interaction of the key regulators. حسب Kankana Bhattacharjee (20623639)

"…Our analysis revealed 33 key regulators were predominantly enriched in neuroactive ligand-receptor interaction, Cell adhesion molecules, Leukocyte transendothelial migration pathways; positive regulation of cell proliferation, positive regulation of protein kinase B signaling biological functions; G-protein beta-subunit binding, receptor binding molecular functions etc. …"

MCCN Case Study 2 - Spatial projection via modelled data حسب Donald Hobern (21435904)

"…This repository contains Jupyter notebooks to demonstrate the functionality of the MCCN data cube components.</p><p dir="ltr">The dataset contains input files for the case study (source_data), RO-Crate metadata (ro-crate-metadata.json), results from the case study (results), and Jupyter Notebook (MCCN-CASE 2.ipynb)</p><h4><b>Research Activity Identifier (RAiD)</b></h4><p dir="ltr">RAiD: https://doi.org/10.26292/8679d473</p><h4><b>Case Studies</b></h4><p dir="ltr">This repository contains code and sample data for the following case studies. …"

DataSheet1_Identification of novel markers for neuroblastoma immunoclustering using machine learning.zip حسب Longguo Zhang (20105238)

"…Three machine learning algorithms (LASSO, SVM-RFE, and Random Forest) were used to screen biomarkers and synthesize their function in neuroblastoma.…"

<b>Rethinking neighbourhood boundaries for urban planning: A data-driven framework for perception-based delineation</b> حسب Shubham Pawar (22471285)

"…</p><p dir="ltr"><b>Input:</b></p><ul><li><code>raw_data/glasgow_open_built/glasgow_open_built_areas.shp</code> - Grid defining sampling points</li></ul><p dir="ltr"><b>Command:</b></p><pre><pre>python svi_module/get_svi_data.py<br></pre></pre><p dir="ltr"><b>Output:</b></p><ul><li><code>svi_module/svi_data/svi_info.csv</code> - Image metadata (IDs, coordinates)</li><li><code>svi_module/svi_data/images/</code> - Downloaded street view images</li></ul><h3>Step 2: Predict Perceptions</h3><p dir="ltr">Use pre-trained deep learning models to predict perceptual qualities (safety, beauty, liveliness, etc.) from street view images.…"

Code حسب Baoqiang Chen (21099509)

"…We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …"

Core data حسب Baoqiang Chen (21099509)

"…We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …"

Image 1_Exploring the role of neutrophil extracellular traps in neuroblastoma: identification of molecular subtypes and prognostic implications.tif حسب Can Qi (540350)

"…Univariate Cox analysis and the LASSO algorithm were used to identify biomarkers for prognosis. …"