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  • šŸ”­ Iā€™m currently working on spatial transcriptomics.
  • šŸ’¬ Ask me about cell typing in single-cell genomics and functional domain detection in spatial transcriptomics.
  • šŸ“« How to reach me: let it be.
  • āš” Fun facts: a lifelong Ph.D. candidate in Marathon, reading, fishing, etc.

Wenjing Ma's Projects

android-common icon android-common

Android common lib, include ImageCache, HttpCache, DropDownListView, DownloadManager, Utils and so on

bart-web icon bart-web

Predict functional transcription factors leveraging H3K27ac profiles and ChIP-seq TF binding datasets.

bart2 icon bart2

Revised version using adaptive lasso model to predict functional transcription factors from a gene list or a ChIP-seq binding profile.

bartweb_jump icon bartweb_jump

Receive the Amazon SQS Service and trigger the shell script.

bmi500_hw3 icon bmi500_hw3

HW3-clustering algorithm implement for course BMI500

bsslecture icon bsslecture

Simplified illustration of blind-source separation algorithms

cellcano icon cellcano

Supervised cell type identification for scATAC-seq data

dec-keras icon dec-keras

Keras implementation for Deep Embedding Clustering (DEC)

deid2020 icon deid2020

Class project for de-identification BMI 500 all 2020

locationinfo icon locationinfo

Android project. Get location info by GPS, Wi-Fi, telephony and Bluetooth.

lrcell icon lrcell

The goal of LRcell is to identify specific sub-cell types that drives the changes observed in a bulk RNA-seq differential gene expression experiment. To achieve this, LRcell utilizes sets of cell marker genes acquired from single-cell RNA-sequencing (scRNA-seq) as indicators for various cell types in the tissue of interest. Next, for each cell type, using its marker genes as indicators, we apply Logistic Regression on the complete set of genes with differential expression p-values to calculate a cell-type significance p-value. Finally, these p-values are compared to predict which one(s) are likely to be responsible for the differential gene expression pattern observed in the bulk RNA-seq experiments.

lrcelltypemarkers icon lrcelltypemarkers

This is an external data storage package for LRcell R package using AnnotationHub.

marvinquiet.github.io icon marvinquiet.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

pytorch-adda icon pytorch-adda

A PyTorch implementation for Adversarial Discriminative Domain Adaptation

refconstruction_supervisedcelltyping icon refconstruction_supervisedcelltyping

Source code for "Evaluation of some aspects in supervised cell type identification for single-cell RNA-seq: classifier, feature selection, and reference construction".

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