chrischen1

EnQA

A 3D-equivariant neural network for protein structure accuracy estimation

GNET2

Gene regulatory network modeling tool (GNET2)

InteractiveNetworks

Web tool for interactive gene network analysis and visualization.

InterpretContactMap

Deep learning methods for interpreting protein contact maps

keras_svcca

neu-cs5800

Code for CS5800 that I teach at Northeastern University.

phospho_network

Regression Model Based on Prior Network Knowledge

pl_test

pl_test

Ratio-Distribution-Analysis-Demo

Software implementation for The Gene Balance Hypothesis: Dosage effects in plant

rnaseq

chrischen1/GNET2

Gene regulatory network modeling tool (GNET2)

chrischen1/EnQA

A 3D-equivariant neural network for protein structure accuracy estimation

chrischen1/InteractiveNetworks

Web tool for interactive gene network analysis and visualization.

chrischen1/InterpretContactMap

Deep learning methods for interpreting protein contact maps

chrischen1/keras_svcca

chrischen1/neu-cs5800

Code for CS5800 that I teach at Northeastern University.

chrischen1/phospho_network

Regression Model Based on Prior Network Knowledge

chrischen1/pl_test

pl_test

chrischen1/Ratio-Distribution-Analysis-Demo

Software implementation for The Gene Balance Hypothesis: Dosage effects in plant

chrischen1/rnaseq

chrischen1/alphafold

Open source code for AlphaFold.

chrischen1/bcbio

scripts for bcbio RNASeq analysis pipeline

chrischen1/cell_cycle_reporter

chrischen1/conversion_tools

A repository for demo collections

chrischen1/DeepGRN

Deep learning for modeling gene regulatory network

chrischen1/FactorNet

A deep learning package for predicting TF binding

chrischen1/Finalproject-XinHero-

chrischen1/Gene4x

Community detection on gene multiplex

chrischen1/gitignore

A collection of useful .gitignore templates

chrischen1/GNET2_benchmark

Data and code for benchmark of GNET2

chrischen1/markdown_readme

Markdown - you can mark up titles, lists, tables, etc., in a much cleaner, readable and accurate way if you do it with HTML.

chrischen1/msda

chrischen1/Numpy_and_MNIST_With_Convolution_networks

This is a simple demo for convolution neural networks with Numpy only on Python. The sample inputs are from MINST.

chrischen1/se3-transformer-public

code for the SE3 Transformers paper: https://arxiv.org/abs/2006.10503

chrischen1/Simple-Implementation-of-ML-Algorithms

My simplest implementations of common ML algorithms

chrischen1/viper_copy

chrischen1/viper_infer

Example scripts for VIPER inferences