bijux-proteomics-intelligence 0.3.1

Policy-driven candidate ranking and scenario decision intelligence for protein progression and portfolio prioritization

bijux-proteomics-intelligence

Package Family

bijux-proteomics-intelligence transforms program intent and evidence posture into policy-governed candidate rankings, scenario recommendations, and decision outputs with explicit explainability and risk signals.

Use this package when you need transparent prioritization logic, rejection reasoning, and portfolio-aware progression guidance for protein design.

Why teams pick this package

• policy-first ranking and recommendation outputs with traceable decision rationale
• scenario evaluators that support progression, redesign, and portfolio balancing
• structured rejection reasons and explainability fields for review conversations
• deterministic scoring patterns suitable for governance and automation

Typical use cases

• rank candidate proteins against defined decision policies
• generate scenario recommendations for advancement or redesign
• produce explainable shortlists for expert review boards
• aggregate portfolio-level signals for sequencing and prioritization

Installation

pip install bijux-proteomics-intelligence

Quick start

from bijux_proteomics_intelligence import briefs, policies, evaluators

Package boundaries

This package owns decision intelligence, ranking policy, scenario scoring, and explainability outputs.

It does not own stage transition authority, evidence ingestion contracts, or lab execution scheduling.

Source guide

• src/bijux_proteomics_intelligence/briefs.py for design brief construction and ranking behavior
• src/bijux_proteomics_intelligence/policies.py for ranking and decision policy models
• src/bijux_proteomics_intelligence/evaluators.py for scenario and portfolio evaluators
• tests for executable behavior expectations

Documentation

• Architecture
• Boundaries
• Contracts
• PyPI maintainer notes