Browse ORBilu by Open Access
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ORBilu is a project developed by
   PredictProtein - Predicting Protein Structure and Function for 29 Years; ; et al in Nucleic Acids Research (2021) Since 1992 PredictProtein (https://predictprotein.org) is a one-stop online resource for protein sequence analysis with its main site hosted at the Luxembourg Centre for Systems Biomedicine (LCSB) and ... [more ▼] Since 1992 PredictProtein (https://predictprotein.org) is a one-stop online resource for protein sequence analysis with its main site hosted at the Luxembourg Centre for Systems Biomedicine (LCSB) and queried monthly by over 3,000 users in 2020. PredictProtein was the first Internet server for protein predictions. It pioneered combining evolutionary information and machine learning. Given a protein sequence as input, the server outputs multiple sequence alignments, predictions of protein structure in 1D and 2D (secondary structure, solvent accessibility, transmembrane segments, disordered regions, protein flexibility, and disulfide bridges) and predictions of protein function (functional effects of sequence variation or point mutations, Gene Ontology (GO) terms, subcellular localization, and protein-, RNA-, and DNA binding). PredictProtein's infrastructure has moved to the LCSB increasing throughput; the use of MMseqs2 sequence search reduced runtime five-fold (apparently without lowering performance of prediction methods); user interface elements improved usability, and new prediction methods were added. PredictProtein recently included predictions from deep learning embeddings (GO and secondary structure) and a method for the prediction of proteins and residues binding DNA, RNA, or other proteins. PredictProtein.org aspires to provide reliable predictions to computational and experimental biologists alike. All scripts and methods are freely available for offline execution in high-throughput settings. [less ▲] Detailed reference viewed: 69 (1 UL)A draft network of ligand–receptor-mediated multicellular signalling in human; ; et al in Nature Communications (2015), 6 Cell-to-cell communication across multiple cell types and tissues strictly governs proper functioning of metazoans and extensively relies on interactions between secreted ligands and cell-surface ... [more ▼] Cell-to-cell communication across multiple cell types and tissues strictly governs proper functioning of metazoans and extensively relies on interactions between secreted ligands and cell-surface receptors. Herein, we present the first large-scale map of cell-to-cell communication between 144 human primary cell types. We reveal that most cells express tens to hundreds of ligands and receptors to create a highly connected signalling network through multiple ligand–receptor paths. We also observe extensive autocrine signalling with approximately two-thirds of partners possibly interacting on the same cell type. We find that plasma membrane and secreted proteins have the highest cell-type specificity, they are evolutionarily younger than intracellular proteins, and that most receptors had evolved before their ligands. We provide an online tool to interactively query and visualize our networks and demonstrate how this tool can reveal novel cell-to-cell interactions with the prediction that mast cells signal to monoblastic lineages via the CSF1–CSF1R interacting pair. [less ▲] Detailed reference viewed: 189 (9 UL) |
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