Web Servers Packages
MEGA: A python package for identifying intratumoral microbes from the ORIEN dataset. (2023)
MICAH: An explainable graph neural framework to identify cancer-associated intratumoral microbial communities. (2023)
MAPLE: Bayesian spatial finite mixture models for identification of cell sub-populations in multi-sample spatial transcriptomics experiments. (2023)
SPRUCE: A suite of Bayesian multivariate finite mixture models for clustering single cell spatial transcriptomics data. (2023)
BANYAN: Bayesian network models for spatially-resolved single-cell data. (2023)
SpaGFT: Graph fourier transformer for representation, analysis, and interpretation of spatially variable genes. (2023)
DeepMAPS: Single-cell biological network inference using a heterogeneous graph transformer. (2022)
scDEAL: Deep Transfer Learning of Drug Sensitivity by Integrating Bulk and Single-cell RNA-seq data. (2022)
scGNN 2.0: a graph neural network tool for imputation and clustering of single-cell RNA-Seq data. (2022)
IDAM: Inference of disease-associated microbial gene modules based on metagenomic and metatranscriptomic data. (2022)
RESEPT: A deep-learning framework for characterizing and visualizing tissue architecture from spatially resolved transcriptomics. (2022)
scREAD protocol: Use of scREAD to Explore and Analyze Single-cell and Single-nucleus RNA-Seq data for Alzheimer’s Disease. (2021)
IRIS-FGM: an integrative single-cell RNA-Seq interpretation system for functional gene module analysis. (2021)
GitHub Publication Bioconductor
scGNN: a novel graph neural network framework for single-cell RNA-Seq analyses. (2021)
GitHub Publication scGNN online website
SeqATU: Predicting ATUs (alternative transcription units) of bacterial organisms. (2020)
LTMG: A novel statistical modeling of transcriptional expression states in single-cell RNA-Seq data. (2019)
DESSO: Prediction of regulatory motifs from human Chip-sequencing data using a deep learning framework. (2019)
QUBIC2.0: A novel and robust biclustering algorithm for analyses and interpretation of large-scale RNA-Seq data. (2019)
rSeqTU: A Machine-Learning Based R Package for Prediction of Bacterial Transcription Units. (2019)
MetaQUBIC a computational pipeline for gene-level functional profiling of metagenome and metatranscriptome. (2019)
EL-SMURF: An Ensemble Learning of SMOTE for Unbalancing samples and RF algorithm in PPI sites prediction. (2019)
GeneQC: A tool for gene expression level quality control. (2018)
SPP: A sigma-54 promoter predictor in prokaryotic genomes based on a machine learning method. (2018)
ViDGER: An R package for interpretation of differential gene expression results of RNA-seq data. (2018)
QUBIC-R package (2017)
GitHub Bioconductor Video Demonstration Publication
A phylogenetic model for understanding the effect of gene duplication on cancer progression. (2014)
Cancer-evolution: A phylogenetic model for understanding the effect of gene duplication on cancer progression. (2013)
supercoil: Bacterial chromosome folding structure under different conditions. (2013)
GitHub Google Code Publication
BoBro 2.0: An integrated toolkit for prediction and analysis of cis-regulatory motifs. (2011, 2013)
GitHub Publication(1.0) Publication(2.0)
GOST: An orthology mapping tool for prokaryotes. (2011)
GitHub Google Code Publication
QUBIC: A biclustering tool for microarray data. (2009)
UberOperon: Detecting uber-operons in prokaryotic genomes