Cell number of gene cluster. حسب Litian Han (17350823)

"…Additionally, we implemented methods to identify conserved pseudotemporal gene modules across multiple samples. …"

Description of clusters in Differential Altas. حسب Litian Han (17350823)

"…Additionally, we implemented methods to identify conserved pseudotemporal gene modules across multiple samples. …"

Transcription clusters list in Fig 3E. حسب Litian Han (17350823)

"…Additionally, we implemented methods to identify conserved pseudotemporal gene modules across multiple samples. …"

Supplementary Data: Biodiversity and Energy System Planning - Queensland 2025 حسب Andrew Rogers (17623239)

"…</li></ul><h3>Analysis Scripts</h3><p dir="ltr">Complete set of R scripts for reproducing all analyses:</p><ul><li><b>percent cost increase_line plot.R</b>: Creates visualizations of energy cost impacts under different conservation scenarios</li><li><b>Zonation curves.R</b>: Generates conservation performance curves and coverage statistics</li><li><b>NPV_bar_plot.R</b>: Produces economic analysis plots with Net Present Value breakdowns</li><li><b>domestic_export_map_iterations.R</b>: Creates spatial maps of renewable energy infrastructure for domestic and export scenarios</li></ul><h2>Technical Specifications</h2><h3>Data Formats</h3><ul><li><b>Spatial Data</b>: ESRI Geodatabase (.gdb), Shapefile (.shp), GeoTIFF (.tif)</li><li><b>Tabular Data</b>: CSV, Microsoft Excel (.xlsx, .xls)</li><li><b>Analysis Code</b>: R scripts (.R)</li></ul><h3>Software Requirements</h3><ul><li><b>R</b> (≥4.0.0) with packages: sf, dplyr, ggplot2, readr, readxl, tidyr, furrr, ozmaps, ggpattern</li><li><b>ESRI ArcGIS</b> or <b>QGIS</b> for geodatabase access and spatial analysis</li><li><b>Zonation</b> conservation planning software (for methodology understanding)</li></ul><h3>Hardware Recommendations</h3><ul><li><b>RAM</b>: 16GB minimum (32GB recommended for full spatial analysis)</li><li><b>Storage</b>: 15GB free space for data extraction and processing</li><li><b>CPU</b>: Multi-core processor recommended for parallel processing scripts</li></ul><h2>Detailed Description of the VRE Siting and Cost-Minimization Model</h2><p><br></p><p dir="ltr">This section provides an in-depth description of the Variable Renewable Energy (VRE) siting model, including the software, the core algorithm, and the optimisation process used to determine the least-cost, spatially constrained development trajectory for VRE infrastructure in Queensland, Australia.…"

A Machine Learning Model for the Proteome-Wide Prediction of Lipid-Interacting Proteins حسب Jonathan Chiu-Chun Chou (22184735)

"…SLiPP is fast and does not require substantial computational resources. Use of the algorithm to detect lipid binding proteins in various proteomes produced hits annotated or verified as bona fide lipid binding proteins. …"

A Machine Learning Model for the Proteome-Wide Prediction of Lipid-Interacting Proteins حسب Jonathan Chiu-Chun Chou (22184735)

"…SLiPP is fast and does not require substantial computational resources. Use of the algorithm to detect lipid binding proteins in various proteomes produced hits annotated or verified as bona fide lipid binding proteins. …"

A Machine Learning Model for the Proteome-Wide Prediction of Lipid-Interacting Proteins حسب Jonathan Chiu-Chun Chou (22184735)

"…SLiPP is fast and does not require substantial computational resources. Use of the algorithm to detect lipid binding proteins in various proteomes produced hits annotated or verified as bona fide lipid binding proteins. …"

A Machine Learning Model for the Proteome-Wide Prediction of Lipid-Interacting Proteins حسب Jonathan Chiu-Chun Chou (22184735)

"…SLiPP is fast and does not require substantial computational resources. Use of the algorithm to detect lipid binding proteins in various proteomes produced hits annotated or verified as bona fide lipid binding proteins. …"

A Machine Learning Model for the Proteome-Wide Prediction of Lipid-Interacting Proteins حسب Jonathan Chiu-Chun Chou (22184735)

"…SLiPP is fast and does not require substantial computational resources. Use of the algorithm to detect lipid binding proteins in various proteomes produced hits annotated or verified as bona fide lipid binding proteins. …"

A Machine Learning Model for the Proteome-Wide Prediction of Lipid-Interacting Proteins حسب Jonathan Chiu-Chun Chou (22184735)

"…SLiPP is fast and does not require substantial computational resources. Use of the algorithm to detect lipid binding proteins in various proteomes produced hits annotated or verified as bona fide lipid binding proteins. …"

A Machine Learning Model for the Proteome-Wide Prediction of Lipid-Interacting Proteins حسب Jonathan Chiu-Chun Chou (22184735)

"…SLiPP is fast and does not require substantial computational resources. Use of the algorithm to detect lipid binding proteins in various proteomes produced hits annotated or verified as bona fide lipid binding proteins. …"

A Machine Learning Model for the Proteome-Wide Prediction of Lipid-Interacting Proteins حسب Jonathan Chiu-Chun Chou (22184735)

"…SLiPP is fast and does not require substantial computational resources. Use of the algorithm to detect lipid binding proteins in various proteomes produced hits annotated or verified as bona fide lipid binding proteins. …"