Quantitative Morphological Signatures Define Local Signaling Networks Regulating Cell Morphology

Bakal*, Aach*, Church, Perrimon

Science 316:1753

Supplemental Materials

June 22, 2007

Abstract

Although classical genetic and biochemical approaches have identified hundreds of unique proteins that function in the dynamic remodeling of cell shape in response to upstream signals, there is currently little systems-level understanding of the organization and composition of signaling networks that regulate cell morphology. We have developed quantitative morphological profiling methods to systematically query the role of individual genes in the regulation of cell morphology in a fast, robust, and cost-efficient manner. Here we analyze a compendium of quantitative morphological signatures (QMSes), and describe the existence of local signaling networks that act to regulate cell protrusion, adhesion, and tension.

* = contributed equally

This Supplemental Materials web page presents software and computer-readable data files additional to the Supporting Online Material available from the journal web site.

  1. CellSegmenter program download, and documentation
  2. Normalized feature scores for all cells.
  3. Means and standard deviations of feature scores for all Treatment Conditions.
  4. Neural Network scores for all cells.
  5. Neural network Z scores (NNZes) for all Treatment Conditions.
  6. Best Neural Network definitions.

Please contact John Aach with any questions or issues.

Copyright (c) 2007 by John Aach and the President and Fellows of Harvard University