Updates
Perspectives and deep dives on the models powering AI for life science discovery.
Updates
This update enables medicinal chemists and computational scientists to rapidly estimate the aqueous solubility of small molecules directly within Vecura, streamlining ADMET profiling and library triage without the need for complex local infrastructure.
Updates
This integration enables researchers and bioinformaticians to easily generate advanced gene-level embeddings from single-cell RNA-seq data within the Vecura platform, bypassing the need for complex deep-learning infrastructure.
Updates
Drug discovery professionals and computational chemists can now explore chemical space and optimize lead scaffolds using the MoFlow generative model, all through a streamlined, infrastructure-free workflow on Vecura.
Updates
This update allows antibody engineers and researchers to instantly assess the developability of their nanobody candidates through a streamlined, guided workflow on Vecura, removing the need for local software configuration.
Updates
This update empowers computational immunologists and antibody engineers to seamlessly characterize, rank, and classify antibody sequences through a streamlined workflow on Vecura, eliminating the need for complex local infrastructure setup.
Updates
Researchers can now leverage the LICHEN generative model directly within Vecura to design, generate, and score compatible antibody light-chain sequences without the need for complex local infrastructure.
Updates
This update enables computational biologists and protein engineers to perform large-scale protein functional annotation through an intuitive workflow inside Vecura, eliminating the need to set up complex deep learning environments or manage model weights manually.
Updates
This update empowers biochemists and pharmaceutical researchers to perform rapid, structure-based pKa and pH-dependent stability predictions through a streamlined workflow on Vecura, eliminating the need for complex local software installation.
Updates
This update enables biologists and protein engineers to perform high-fidelity sequence analysis and fitness prediction through a streamlined workflow on Vecura, eliminating the need to manage complex, resource-heavy model deployment.
Updates
This update enables structural biologists and computational researchers to generate high-fidelity protein structural embeddings through a streamlined, automated workflow on Vecura, eliminating the need to manage complex environment dependencies or custom preprocessing pipelines.
Updates
This integration enables bioinformaticians and molecular biologists to perform advanced pathway enrichment analysis and gene ID conversion through a streamlined, guided workflow on Vecura, eliminating the need for complex local infrastructure or legacy software dependencies.
Updates
This update empowers medicinal chemists and drug discovery scientists to rapidly evaluate the pharmacokinetic and toxicity profiles of small molecules directly within Vecura, streamlining the lead optimization process without the need for manual model deployment.