更新
关于驱动生命科学探索 AI 的模型的观点与深度解析
产品更新
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.
产品更新
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.
产品更新
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.
产品更新
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.
产品更新
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.
产品更新
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.
产品更新
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.
产品更新
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.
产品更新
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.
产品更新
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.
产品更新
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.
产品更新
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.