Projects in Awesome Lists tagged with standardisation
A curated list of projects in awesome lists tagged with standardisation .
https://github.com/nbisweden/agat
Another Gtf/Gff Analysis Toolkit https://nbisweden.github.io/AGAT/
agat gff gff-format gtf perl-scripts standardisation toolkit
Last synced: 06 Jan 2026
https://github.com/NBISweden/AGAT
Another Gtf/Gff Analysis Toolkit
agat gff gff-format gtf perl-scripts standardisation toolkit
Last synced: 05 May 2025
https://github.com/Al-Murphy/MungeSumstats
Rapid standardisation and quality control of GWAS or QTL summary statistics
bioconductor-package bioinformatics database-api genomics gwas qtl r r-package standardisation summary-statistics vcf-files
Last synced: 29 Jul 2025
https://github.com/al-murphy/mungesumstats
Rapid standardisation and quality control of GWAS or QTL summary statistics
bioconductor-package bioinformatics database-api genomics gwas qtl r r-package standardisation summary-statistics vcf-files
Last synced: 07 Apr 2025
https://github.com/neuroml/documentation
Source repository for NeuroML documentation.
computational-modelling computational-neuroscience neuroscience standardisation
Last synced: 29 Jul 2025
https://github.com/nutriverse/anthrocheckr
An Implementation of Anthropometric Measurement Standardisation Tests
Last synced: 23 Jan 2026
https://github.com/neuroml/neuroml_api
C++ API for NeuroML 2
combine computational-modelling computational-neuroscience neuroml standardisation
Last synced: 28 Apr 2025
https://github.com/cjabradshaw/savannacorridors
Analysis of palaeoecological records across South-East Asia to determine the evidence for regime shifts between open savannas and dense tropical forests occurred since the Last Glacial Maximum
biome correlation ecological-resilience last-glacial-maximum palynology resampling savanna savanna-corridor south-east-asia spatial-autocorrelation standardisation
Last synced: 21 Feb 2026
https://github.com/elmezianech/food-delivery-time-prediction
This machine learning project focused on predicting food delivery times. The code emphasizes essential tasks such as data cleaning, feature engineering, categorical feature encoding, data splitting, and standardization to establish a solid foundation for building a robust predictive model.
artificial-intelligence cross-validation data-cleaning data-extraction decision-tree-regression feature-engineering labelencoder linear-regression machine-learning mae ml model-building mse r2-score random-forest-regression regression rmse standardisation xgboost-regression
Last synced: 06 Jun 2026
