| { |
| "field_id": "F037", |
| "field": "computational biology", |
| "directions": [ |
| { |
| "direction_id": "G0", |
| "name": "Small-molecule design and optimization", |
| "scope": "Generate or modify candidate small molecules to satisfy design constraints such as protein targets, structural exemplars, or properties. Encompasses both target-guided and non-target-led design." |
| }, |
| { |
| "direction_id": "G1", |
| "name": "Protein and antibody design", |
| "scope": "Propose protein sequences and candidate antibodies with desired structures, properties, or binding capabilities. Includes the full range of antibody sequence, structure, and antigen-interface design." |
| }, |
| { |
| "direction_id": "G2", |
| "name": "Sequence-based microbial identification", |
| "scope": "Identify origins, pathogens, hosts, or types from microbial or viral sequence evidence." |
| }, |
| { |
| "direction_id": "G3", |
| "name": "Biological interaction characterization", |
| "scope": "Infer relationships between biological entities or characterize where binding occurs and how strong it is. Collectively encompasses unknown network edges, protein–small-molecule binding strength, and localization of protein binding residues; an individual study need not produce all of these outputs." |
| }, |
| { |
| "direction_id": "G4", |
| "name": "Protein structure inference from sequence", |
| "scope": "Infer protein structural features or folds from given amino-acid sequences, and improve the inputs and combinations of predictors used for that inference." |
| }, |
| { |
| "direction_id": "G5", |
| "name": "Genomic regulatory modeling", |
| "scope": "Identify regulatory sequence features and model their relationships to epigenetic states or gene expression." |
| }, |
| { |
| "direction_id": "G6", |
| "name": "Functional and activity annotation of biological entities", |
| "scope": "Assign attributes such as function or activity to existing genes, gene sets, proteins, or peptides. Encompasses entity annotation using network evidence and protein and peptide property prediction using sequence evidence." |
| }, |
| { |
| "direction_id": "G7", |
| "name": "Genomic and transcriptomic marker discovery", |
| "scope": "Select compact sets of variants or genes indicative of phenotypes, cell identity, or biological states, including research on the stability of that selection." |
| }, |
| { |
| "direction_id": "G8", |
| "name": "Single-cell representation and integration", |
| "scope": "Recover reusable latent cell structure from single-cell molecular profiles and relate datasets, cell populations, or modalities." |
| }, |
| { |
| "direction_id": "G9", |
| "name": "Small-molecule property prediction", |
| "scope": "Learn chemical representations or similarities of existing small molecules to predict their properties." |
| }, |
| { |
| "direction_id": "G10", |
| "name": "Molecular prediction of treatment response", |
| "scope": "Use drug, genomic, or longitudinal molecular information to predict treatment effectiveness in cellular or patient contexts, rather than molecular binding alone." |
| } |
| ] |
| } |
|
|
