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protein-protein interaction (PPI) networks. GCN inference relies on the popular

BgeeCall allows to generate present/absent gene expression calls without using

protein-protein interactions), by including network-based regularizers. glmSparseNet uses

protein domain-based approach and; iii. synteny detection using synteny

Computes Multiple Co-Inertia Analysis (MCIA), a dimensionality reduction (jDR

proteins with potential clinical associations. From CNA and RNA-seq data

Protein coding genes from a list of candidates. Systematically download

protein sequences and classify them based on their modes of duplication

protein sequences and analyze them. Anchor pairs are detected with

protein markers at the single-cell level, producing high dimensional

protein products). The network is scanned using SConES, which looks

protein coding genes. FGGA embodies elements of predicate logic, communication

protein sequence data and classify them into families and subfamilies

magrene allows the identification and analysis of graph motifs in

protein databases based on user-submitted genomic variants, splice-junctions

proteins (Y), to infer a matrix of molecular protein dependencies

protein-coding genes, distal enhancers, and genes encoding microRNAs and lncRNAs

protein and gene information can be searched for using the API. Methods

proteins from multi-omics' data (MOMA) algorithm, as well as ancillary

analysis of thermal proteome profiles reveals novel drug-binding proteins.

protein complex assembly and (differential) protein-protein interactions across conditions

protein interactions from 2D thermal profiles (DLPTP), Performs an FDR-controlled