Pinned Repositories
3ca
Code for reproducing the analysis in Gavish et al. "The transcriptional hallmarks of intra-tumor heterogeneity across a thousand tumors".
awesome-deep-learning-single-cell-papers
ceres-solver
A large scale non-linear optimization library
DeepLM
DeepLM: Large-scale Nonlinear Least Squares on Deep Learning Frameworks using Stochastic Domain Decomposition (CVPR 2021)
deepsomatic
DeepSomatic is an analysis pipeline that uses a deep neural network to call somatic variants from tumor-normal sequencing data.
dpa-analysis
Nextflow Pipeline for the analysis of Double Progressive Alignment (DPA)
edward
A library for probabilistic modeling, inference, and criticism. Deep generative models, variational inference. Runs on TensorFlow.
FDRnet
A method for identifying significantly mutated subnetworks in human diseases
fnc-extras
Extra materials for *Fundamentals of Numerical Computation* by Driscoll and Braun.
FriendsDontLetFriends
Friends don't let friends make certain types of data visualization - What are they and why are they bad.
yangle293's Repositories
yangle293/FDRnet
A method for identifying significantly mutated subnetworks in human diseases
yangle293/3ca
Code for reproducing the analysis in Gavish et al. "The transcriptional hallmarks of intra-tumor heterogeneity across a thousand tumors".
yangle293/awesome-deep-learning-single-cell-papers
yangle293/ceres-solver
A large scale non-linear optimization library
yangle293/DeepLM
DeepLM: Large-scale Nonlinear Least Squares on Deep Learning Frameworks using Stochastic Domain Decomposition (CVPR 2021)
yangle293/deepsomatic
DeepSomatic is an analysis pipeline that uses a deep neural network to call somatic variants from tumor-normal sequencing data.
yangle293/dpa-analysis
Nextflow Pipeline for the analysis of Double Progressive Alignment (DPA)
yangle293/edward
A library for probabilistic modeling, inference, and criticism. Deep generative models, variational inference. Runs on TensorFlow.
yangle293/fnc-extras
Extra materials for *Fundamentals of Numerical Computation* by Driscoll and Braun.
yangle293/generative-ai-for-beginners
12 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
yangle293/goatools
Python scripts to find enrichment of GO terms
yangle293/locfdr-python
Python implementation of Efron, Turnbull, and Narasimhan's R function locfdr v1.1-7, which computes local false discovery rates. See http://cran.r-project.org/web/packages/locfdr/ for more information.
yangle293/MultiFDRnet
An algorithm to detect significantly disrupted subnetwork using multiplex networks.
yangle293/Multilayer-networks-library
yangle293/HOPE
SIGMOD 2024 paper titled "Efficient High-Quality Clustering for Large Bipartite Graphs"
yangle293/IR-query-clustering
yangle293/local-densely-connected-clusters
Code to accompany the paper "Local Algorithms for Finding Densely Connected Clusters", published at ICML 2021.
yangle293/LocalGraphClustering
yangle293/Personalized_PCA
An implementation for personalized PCA
yangle293/protein-sequence-embedding-iclr2019
Source code for "Learning protein sequence embeddings using information from structure" - ICLR 2019
yangle293/pytorch-minimize
Newton and Quasi-Newton optimization with PyTorch
yangle293/qpsolvers
Quadratic Programming solvers in Python with a unified API
yangle293/RBM-DP-Experiment
Simplistic RBM and DP
yangle293/scRNAseq-analysis-notes
scRNAseq analysis notes from Ming Tang
yangle293/SharePathway
a python package for KEGG pathway enrichment analysis with multiple gene lists.
yangle293/SNLLS
Stochastic Nonlinear Least-Squares for Large-Scale Machine Learning
yangle293/specgreedy
Unified Dense Subgraph Detection Algorithms: **Best student DM paper award in ECML-PKDD'20**
yangle293/TSgraph
yangle293/xylearn
A simplified version of pylearn2