WebProteinSolver. ProteinSolver our graph neural network algorithm for designing novel proteins. Try it out with your own distance matrix or use a given distance matrix to swiftly generate proteins that will fold into the given shape! WebELASPIC uses a wide range of sequential and structural features to predict the change in the Gibbs free energy for protein folding and protein-protein interactions. It can be used both through a web server and as a stand-alone application.

Computational Analysis of Deleterious Single Nucleotide …

WebELASPIC is a novel ensemble machine-learning approach that predicts the effects of mutations on protein folding and protein-protein interactions. Here, we present the … WebNov 23, 2024 · ELASPIC:: DESCRIPTION. ELASPIC constructs homology models of domains and domain-domain interactions, and uses those models, together with sequential and other features, to predict the energetic impact of a mutation on the stability of a single domain or the affinity between two domains.::DEVELOPER. Kim Lab:: SCREENSHOTS. … dj5871-010

Philip KIM Professor (Associate) Ph.D. - ResearchGate

WebWhatsApp Web. Use WhatsApp on your computer. Open WhatsApp on your phone; Tap Menu or Settings and select Linked Devices; Tap on Link a Device; Point your phone to this screen to capture the QR code; Tutorial. Need help to … WebJun 2, 2016 · Here we present the ELASPIC web server, which makes the ELASPIC pipeline available through a fast and intuitive interface. The web server can be used to evaluate the effect of mutations on any protein in the Uniprot database, and allows all predicted results, including modeled wild-type and mutated structures, to be managed … Webelaspic. Project ID: 2767924. Star 2. 776 Commits. 1 Branch. 10 Tags. 128.8 MB Project Storage. Ensemble Learning Approach for Stability Prediction of Interface and Core mutations. master. dj5873-010