Division/Committee: [BIOT: Division of Biochemical Technology]

In the past decade, artificial intelligence has had a huge impact on protein design, ranging from AI-guided protein folding and design to large-scale dataset curation and digitization. In this session, we encourage submissions related to novel applications of AI to protein design including novel algorithms and representations, methods for designing products for activity (e.g. binding, enzymatic activity, or other functions), methods for designing products for increased manufacturability or stability, methods for designing products for synthetic biology applications, and methods for design different types of biological products (including proteins and other modalities). We additionally encourage submissions related to integrating experimental and machine learning strategies such as innovations that couple high throughput screening with machine learning or active learning-guided experimental design. Finally, we encourage submissions that explore challenges with curating the datasets required for machine learning such as approaches for curating historical data, combining data from multiple sources, or federated learning techniques.

Varnika Roy

GlaxoSmithKline Plc

Appearances