Bacon: a comprehensive computational benchmarking framework for evaluating targeted chromatin conformation capture-specific methodologies. [Link] [Paper]

The 3D Genome Organization in Disease ( 3dGeOD) is a curated database, through which users can get access to the experimentally supported associations between diseases/phenotypes and 3D Genome architecture changes. [Link]

CSA is developed for the whole process of ChIP-Seq analysis, which covers mapping,quality control,peak calling and downstream analysis.In addition,CSA provides a customization function for users to define their own workflow.Moreover,the visualization of mapping,peak calling, motif finding,and pathway analysis results is also supplied in CSA. [Link]

NID is a comprehensive user-friendly web server for the prioritization and analysis of disease-related (candidate) genes, by which the users can easily get the results of disease-related genes by three search patterns (genomic location, cytogenetic location and whole network genome), subnetwork visualization, enrichment analysis and external links of the genes. [Link] [Paper]

LDAP is a free web server for lncRNA-disease association prediction. It took the input lncRNA sequence in fasta format, either a pasted sequence (length > 200bp) or a file. Then the sequence similarity between input lncRNA and database is calculated by using Smith-Waterman algorithm. [Link] [Paper]

PROBselect suggests a predictor that is likely to provide the best prediction of protein-binding residues the for the input proteins. PROBselect uses predictions generated by SCRIBER and estimated AUC of SSWRF and CRFPPI to make the recommendation. [Link] [Paper]

DeepDISOBind provides predictions of the disordered residues that interact with proteins, DNA and RNA. [Link] [Paper]

DeepPFP-CO uses Graph Convolutional Network to explore and capture the co-occurrence of GO terms to improve the prediction of protein function. [Link]

DeepLncLoc: a deep learning framework for long non-coding RNA subcellular localization prediction based on subsequence embedding. [Link] [Paper]

EP-GBDT: improving human essential protein prediction using only protein sequences via ensemble learning. [Link] [Paper]

NetEPD: an integrated information platform for networkbased essential protein discovery [Link] [Paper]