23andMe, Inc.

Computational techniques and algorithms for processing, aligning, and interpreting raw biological sequence data (DNA, RNA, protein), including identifying genetic variations, classifying organisms, or predicting sequence attributes.

Applying computational methods, often involving machine learning and multiomics data, to design, analyze, and understand biomolecules, genetic sequences, or complex biological systems.

Methods and systems for integrating, transforming, and managing complex or domain-specific data from disparate sources into a unified structure, often for specific applications like social networks, genomics, or business forms.

Design and engineering of proteins or peptides to directly modulate immune responses, including enhancing antigen presentation, suppressing inflammation, or activating specific immune cell types.

Computational methods and systems for analyzing biological data (e.g., genomic, proteomic, clinical) to diagnose diseases, predict patient prognosis, assess treatment response, or stratify patients for therapy.

Design and modification of antibodies or antibody-derived fragments for targeted therapeutic intervention, including bispecific formats, Fc region modifications, and activatable constructs.

Therapeutic interventions that target immune checkpoint pathways to either enhance or suppress immune responses, often used in cancer immunotherapy or autoimmune diseases.

Therapeutic strategies employing nucleic acids (DNA, RNA, oligonucleotides) to modulate gene expression, deliver genetic material, or interfere with disease-causing pathways. Includes gene therapy using viral vectors.

Systems that process data to provide personalized recommendations, predict events, or automate decision-making processes based on learned patterns, user behavior, or environmental factors.

Utilizing machine learning, particularly deep learning, to analyze medical data such as images, sensor readings, or physiological signals for disease prediction, diagnosis, or treatment assessment.