ustc-hilab Goto Github PK

climat

accurate detection of copy number alteration and loss of heterozygosity in impure and aneuploid tumor samples using whole-genome sequencing data

climathet

Detecting subclonal copy number alterations and loss of heterozygosity in heterogeneous tumor samples from whole-genome sequencing data

clonecna

detecting subclonal somatic copy number alterations in heterogeneous tumor samples from whole-exome sequencing data

deepphos

deeptl-ubi

dgpathinter

a novel model for identifying driver genes via knowledge-driven matrix factorization with prior knowledge from interactome and pathways

dmthndm

giant

Genome-wide identification of somatic aberrations from normal-tumor samples

gphmm

hnmdrp

A novel heterogeneous network-based method for drug response prediction in cancer cell lines

in-house

intdriver

Discovering potential driver genes through an integrated model of somatic mutation profiles and gene functional information

learningpancancergene

A novel unsupervised learning model for detecting driver genes from pan-cancer data through matrix tri-factorization framework with pairwise similarity constraints

lpbni

lpihn

Predicting Long N oncoding RNA and Protein Interactions U sing Heterogeneous Network Model

lscdfs-mkl

mcgfinder

A novel network regularized matrix decomposition method to detect mutated cancer genes in tumour samples with inter-patient heterogeneity

mdnnmd

An implementation of multimodal deep neural network, a new model for human breast cancer prognosis prediction.

mptm

MPTM: A Tool for Mining Protein Post-translational Modifications from Literature

nrl2drp

A novel approach for drug response prediction in cancer cell lines via network representation learning

ntsmda

pkis

Computational Identification of Protein Kinases for Experimentally Discovered Protein Phosphorylation Sites

py-faster-rcnn

Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version

rs-expnet-crnmf

Discovering mutated driver genes through a robust and sparse co-regularized matrix factorization framework with prior information from mRNA expression patterns and interaction network

semi-hic

Semi-HIC: A novel semi-supervised deep learning framework for histopathological image classification

thinkstats2

Text and supporting code for Think Stats, 2nd Edition

tpglda

Novel prediction of associations between lncRNAs and diseases via lncRNA-disease-gene tripartite graph

ustc-hilab.github.io

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