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k-TSP: k-Top disjoint Scoring Pairs
The k-TSP algorithm is a novel
machine learning method that seeks to discriminate disease classes by finding pairs
of genes (or proteins or miRNAs) whose expression levels typically invert from one
class to the other (e.g. Cancer versus Normal).
[Abstract]
[Paper]
BiNGS!SL-seq:
Bioinformatics for Next Generation Sequencing - synthetic
lethal screen analysis module
The BiNGS! (Bioinformatics for Next Generation
Sequencing) program is an innovative bioinformatics analysis pipeline for analyzing
and interpreting genome-wide shRNA deep sequencing data
[Abstract]
K-Map: Kinase Connectivity Map
K-Map is a novel and user-friendly web-based program that systematically
connects a set of query kinases to kinase inhibitors based on quantitative profiles of
the kinase inhibitor activities. Users can use K-Map to find kinase inhibitors for a set
of query kinases (obtained from high-throughput "omics" experiments) or to reveal
new interactions between kinases and kinase inhibitors for rational drug combination
studies.
[K-Map Website]
[Abstract]
[Paper]
BEReX:
Biomedical Entity-Relationship eXplorer
BEReX is a new
biomedical knowledge integration, search and exploration tool. BEReX
integrates eight popular databases (STRING, DrugBank, KEGG,
PhamGKB, BioGRID, GO, HPRD and MSigDB) and delineates an integrated
network by combining the information available from these
databases. Users search the integrated network by entering key
words, and BEReX returns a sub-network matching the key words.
The resulting graph can be explored interactively. BEReX allows users
to find the shortest paths between two remote nodes, find the most
relevant drugs, diseases, pathways and so on related to the current
network, expand the network by particular types of entities and relations
and modify the network by removing or adding selected nodes.
BEReX is implemented as a standalone Java application.
[Download BEReX]
[Abstract]
[Paper]
COSSY: COntext-Specific Subnetwork discoverY
COSSY is an algorithm to discover important subnetworks differentiating between two phenotypes (context). It automatically finds differentially expressed subnetworks of closely interacting molecules from molecular interaction networks (such as KEGG or STRING) using gene expression profiles. This is the first non-greedy approach of its kind. COSSY works for any interaction network regardless of the network topology. It can also be used as a highly accurate classification platform. COSSY has been implemented in R.
[Download COSSY]
[Abstract]
[Paper]
DSigDB: Drug Signatures Database for Gene Set Analysis
Drug Signatures Database (DSigDB) is a new gene set resource that relates drugs/compounds and their target genes, for gene set enrichment analysis (GSEA). DSigDB currently holds 22527 gene sets, consists of 17389 unique compounds covering 19531 genes. We also developed an online DSigDB resource that allows users to search, view and download drugs/compounds and gene sets. DSigDB gene sets provide seamless integration to GSEA software for linking gene expressions with drugs/compounds for drug repurposing and translational research.
[DSigDB Website]
[Abstract]
[Paper]
KAR: Kinase Addiction Ranker
Kinase Addiction Ranker (KAR) is an algorithm that integrates high-throughput drug screening data, comprehensive kinase inhibition data and gene expression profiles to identify kinase dependency in cancer cells.
[Download KAR]
[Abstract]
[Paper]