Simplifying Seurat data processing, clustering, and analysis
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Updated
Jan 21, 2023 - R
Simplifying Seurat data processing, clustering, and analysis
Includes a package for rank order clustering and modified rank order clustering proposed by Amruthnath (2016)
Partitioning Clustering Analysis of Vehicles Data
Supervised and unsupervised analysis
identify segments of customers by geography using unsupervised learning
Computational protemics analysis of cancer cell-lines at the level of single-cells
Use of Supervised and Unsupervised Learning Techniques to determine critical components for development of countries
Comparing a climate-based clustering of Scots pine sites with traditional seed zones
A Shiny application for grouping countries into clusters based on the electrical socket types that are available.
Cleaning data entered from the Old Faithful Visitor Center Logs from 2000 so that they're ready for public consumption.
Machine Learning Algorithms for Innovation in Tourism
Identification of clusters of co-expressed genes based on their expression across multiple (replicated) biological samples.
Data science projects
K-means clustering algorithm to group people who live close to each other.
R package containing functions which execute supervised and unsupervised learining on a dataset and give as results the performance metrics of different algorithms.
This work intends to identify, through Principal Component Analysis and Data Clustering Analysis, the profiles of Brazilian municipalities in order to stimulate the debate on the priorities of government actions that emphasize the role of redistributive policies in the light of the distinctive aspects of Brazilian society.
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