BioCCP.jl

BioCCP.jl computes optimal sample sizes for screening experiments in combinatorial biotechnology by applying the Coupon Collector Problem to quantify design-space coverage.

Key Features:

• Coupon Collector Problem (CCP) framework: Implements the CCP mathematical framework to model sampling requirements for design-space coverage.
• Sample-size calculation: Provides functions that calculate the minimum number of samples required to achieve sufficient design-space coverage in screening experiments.
• Combinatorial biotechnology focus: Targets experimental design and coverage analysis specifically for combinatorial biotechnology screening problems.
• Implementation: Implemented as computational functions in the Julia programming language.

Scientific Applications:

• Experimental design in combinatorial biotechnology: Determines sample sizes for screening experiments to maximize coverage and minimize redundancy.
• Synthetic biology, drug discovery, and metabolic engineering: Assists planning of screening experiments in these fields by estimating sample sizes needed to comprehensively explore combinatorial design spaces.

Methodology:

Analyses use the Coupon Collector Problem (CCP) mathematical framework and compute sample-size estimates via functions implemented in Julia.