Name: Estella Yixing Dong
Type: User
Bio: There's always more to learn. Currently doing PhD in Switzerland.
Twitter: nalaotteristic
Location: Lausanne, Switzerland
Blog: estellad.github.io/online-cv
Estella Yixing Dong's Projects
Using a two-step bayesian framework to model ground truth BOLD signal
'Best Practices for Spatial Transcriptomics Analysis with Bioconductor' online book
Stickers for some Bioconductor packages - feel free to contribute and/or modify.
test test ~
Decoding EEG signals using Convolutional Neural Networks
Unified dataset for a better understanding of COVID-19
Deep Clustering for Unsupervised Learning of Visual Features
Modeling pharmacoepidemiological dispensation data as a multiple visit marked point process
A collection of reference documents and files
My Bio
When life gives you lemon, create a repository.
GeoMX analysis workflow
Grouped Discrete Scale for 'ggplot2'
Visualization functions for spatially resolved transcriptomics data
Alternative Visium visualization in R overlayed with H&E, for scatterpie, continuous and categorical variables. The package differs from ggspavis::plot_Visium(), for its independence of storing the H&E image in the SpatialExperiment. Simpler inputs, less automation.
Experimenting with various imaging analysis steps and attempts to customize state-of-the-arts models to biomedical images
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
A repo hosting scirpts to reproduce the analyses in the manuscript.
Leveraging network analysis packages in R to produce an animation of nodes and edges evolving over time.
Estella's online resume
Plot UMAP colored by continuous feature expression level or by categorical clusters
This is a basic stock market predictor built using artificial neural network and implemented in Python.
R for data science: a book
"Learn the rules like a pro, so you can break them like an artist." - Pablo Picasso
Significance analysis for clustering single-cell RNA-sequencing data
R toolkit for single cell genomics
Automate single-cell resolution QC of any Seurat single-cell or spatial object.