A user-friendly website to identify and annotate Disease signals

by linking high-throughput omics Datasets and disease Knowledge

Explore your dataset

3. Input gene list for this disease
Performance of six algorithms across 1750 diseases
(Examples:
)

Brief Introduction

DDK-Linker is a user-friendly website for Linking high-throughput Disease omics Datasets and disease Knowledge based on six well-recognized algorithms, to facilitate the exploration of disease signals in high-throughput screenings.




Disease signals are the most promising, biologically plausible and disease-associated genes in high-throughput disease -omics experimental data (Genome Biol. 2022, Genome Med. 2019). High-throughput experimental approaches such as gene expression microarrays or quantitative proteomics allow researchers to measure thousands of genes, generating hundreds of genes of interest ( GOIs, such as differentially expressed genes/proteins). However, researchers usually select only several genes ( disease signals) for further disease mechanism and drug discovery. Identifying these most valuable and informative disease signals from the massive -omics data is still a great challenge for the current biomedical community. Here, DDK-Linker attempts to alleviate this challenge by linking the -omics data to known disease knowledge. DDK-linker is designed to be a routine bioinformatics tool for the disease -omics experiments. More...

DDK-Linker
was developed at Beijing Proteome Research Center (BPRC).

Browser compatibility:
We support the latest versions of the
Microsoft Edge
,
Chrome
,
Firefox
,
Opera
,
Safari
,
Internet Explorer
(version 10 and 11).

Citation:
Kong X, Diao L, Jiang P,
et al. ,
DDK-Linker: A network-based strategy identifies disease signals by linking high-throughput omics datasets to disease knowledge. 
(submitted to
Briefings in Bioinformatics
)

We gratefully acknowledge DisGeNET, HPRD for their generously sharing of their datasets and algorithm.

This work is funded by the:
National Natural Science Foundation of China [32088101, 32271518,31871341], National key Research and Development Program of China [2016YFC0901905, 2020YFE0202200, 2021YFA1301603] and Program of International S&T Cooperation (2014DFB30020).
      

#2023.12.14 DDK-Linker was submitted to Briefings in Bioinformatics.

#2022.12.01 130 successful analyses have been conducted by outside users.

#2022.06.01 DDK-Linker was officially online for outside users.

#2022.04.01 The underlying disease knowledge graph was expanded to cover 2000 human diseases.

#2022.03.01 Network embedding analysis function was added

#2022.01.01 DDK-Linker starts internal testing, used to find the candidate disease gene by network fusion analysis.