Bowhead

Bowhead estimates concerted cell velocity from time-series wound healing assays to quantify cell migration dynamics independently of wound shape.

Key Features:

• Wound Detection Algorithm: Uses cell confluency thresholding to detect wounds in monolayer assays and identify wound boundaries.
• Bayesian Velocity Estimation: Applies a Bayesian framework to estimate concerted cell velocity and provide an associated likelihood measure.
• Independence from Wound Shape: Tracks cell velocity independently of wound area or shape changes.
• Enhanced Signal-to-Noise Ratio: Focuses on velocity measurements to achieve improved signal-to-noise ratio relative to wound-area-based methods.

Scientific Applications:

• Cancer Research: Quantifies how cell velocity responds to perturbations such as siRNA knockdown to investigate mechanisms of tumor spreading and metastasis formation.
• Basic Cell Biology: Enables analysis of fundamental aspects of cell phenotype and migration in vitro.

Methodology:

Wound detection is performed by cell confluency thresholding, followed by Bayesian estimation of concerted cell velocity with computation of likelihoods.