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-lpi-cch

3dsc-tf

biorfr

cancer_network_control

This packge is a platform to identify personalized driver genes by integrating different single sample network construction methods and different structure based network control principles.

circbdcnn

circBDCNN: distinguishing circular RNAs from other long non-coding RNAs with Broad Dilation Convolutional Neural Network

come

calculate COding potential from Multiple fEatures

constrained_target_controllability

The CTC,is to estimate the ability of a given network to control the targets by choosing driver nodes from the set of the constrained control nodes.

cpgd

deepm6a

A CNN based R function to identify single base m6A site from MeRIP-Seq peak region.

dgmp

dmdeepm6a1.0

A R package used to identify single base resolution m6A and differential m6A methylation site from MeRIP-seq data version 1.0.

dmsc

DMSC: a dynamic multi-seeds method for clustering 16S rRNA sequences into OTUs

dpddi

DPDDI:a Deep Predictor for Drug-Drug Interactions

emogi

An explainable multi-omics graph integration method based on graph convolutional networks to predict cancer genes.

funm6aviewer

Identification and visualization of functional differential m6A methylation genes (FDmMGenes) and single base DmM sites.

gcdn

Deep Graph-Convolutional Image Denoising

gnn-ddi

hgdc

hocnnlb

It is a deep learning method used for predicting the RBP binding sites on lncRNA chains.

hypersynergy

Source code and dataset for TPAMI 2023 paper: "Few-Shot Drug Synergy Prediction with a Prior-Guided Hypernetwork Architecture"

idhi-mirw

imcdriver

irrg

lncrna_mdeep

lpi-cnncp

lpi_bls

m6acancernet

m6AcancerNet is a novel network-based approach to identify m6A-mediated driver genes in cancer.

m6aexpress

m6aexpress-1

m6A-express is a tool to identify m6A methylation significantly regulated expression genes in specific context

m6aexpressbhm

m6Aexpress-BHM: Predicting m6A regulation of gene expression in multiple-groups context by a Bayesian Hierarchical Mixture model