A codon-aware protein modeling research direction for understanding coding-sequence effects.

A foundation-model research direction for stronger position-aware bidirectional sequence modeling.

Synthyra's protein representation model for sequence understanding across Atlas workflows.

Aligns protein, annotation, and language-model representations so biological knowledge can move between spaces.

A low-code platform for evaluating and building protein property prediction workflows.

Connects protein sequences to structured functional annotation space for search, triage, and interpretation.

Prioritizes likely protein-ligand interactions for drug discovery, repurposing, and target exploration.

Maps likely protein-protein interactions from amino acid sequence alone.

Suggests broad enzyme-class hypotheses from protein sequence.

Provides stricter enzyme-function hypotheses when higher-confidence EC assignment is needed.

Prioritizes proteins that are more likely to express successfully in E. coli workflows.

Estimates whether a protein sequence is likely to self-associate as a homodimer.

A set of fast protein property predictors for triaging sequence quality, function, localization, and developability.

Estimates enzyme turnover potential from protein sequence.

Estimates the pH range where a protein may be most compatible or active.

Scores whether a sequence looks like a natural protein rather than random or poorly formed sequence.

Prioritizes protein sequences that are more likely to remain soluble.

Provides a complementary solubility-style readout for protein developability triage.

Predicts likely cellular localization signals from protein sequence.

Estimates taxonomic signal in a protein sequence for context, quality control, and dataset review.

Estimates whether a protein sequence is likely to tolerate higher-temperature conditions.

Turns protein sequences into structured functional annotation hypotheses.

Predicts protein structure and refines difficult cases for Atlas structure views.

Generates and prioritizes protein sequences for design campaigns, including binder discovery.