Louis-Fran├žois Handfield


E-mail : LFHandfield@gmail.com

Phd. in Computer Science (University of Toronto)
M. sc. in Computer Science with Bioinformatic Option (McGill University)
B. sc. Join Honours in Computer Sciences and Mathematics (McGill University)

Publications:


Handfield L. F., Strome B., Chong Y. T. & Moses A. M. (2014). Local statistics allow quantification of cell-to-cell variability from high-throughput microscope images. Bioinformatics 2014 : btu759v1-btu759

Lumba S., Toh S., Handfield L. F., Swan M., Liu R., Youn J. Y., Cutler S. R., Subramaniam R., Provart N., Moses A. M., Desveaux D. & McCourt P. (2014). A Mesoscale Abscisic Acid Hormone Interactome Reveals a Dynamic Signaling Landscape in Arabidopsis. Developmental cell, 29(3), 360-372.

Handfield L. F., Chong Y. T., Simmons J., Andrews B. J. & Moses A. M. (2013). Unsupervised Clustering of Subcellular Protein Expression Patterns in High-Throughput Microscopy Images Reveals Protein Complexes and Functional Relationships between Proteins. PLoS computational biology, 9(6), e1003085.

Ressources:


Hierarchical clustering of Yeast Proteins: Hierarchical organization of 4004 yeast proteins, which displays similarities in protein expression (abundance and subcellular distribution). The tree structure can be browsed online (using java treeview applet).
Table of Single-cell measurements: A total of 1 million cells were identified in an image collection. In that collection, 4004 proteins types were tagged with a green flurescent protein. An list of measurements were used on the green fluorescent pattern found within individual cell areas. These data tables were used in Handfield et al. 2013
Source Code for cell identification in images.: C++ code for many image analysis processes that are combined to detect yeast cells in images. This is designed to identify elliposidal objects that may be found clumped in images. Identified cell areas are analysed so to detect artefacts and misidentified objects throught the use of a confidence score (probability). Processes operate on multi-paged tiff files, and may produce tables of single cell measurements or images with identifed cells, which use pixel intensity to encode cell ID.
DataEater: a (carefully named) program which recovers the orientation of yeast plates within an image, and measure the size of the colonies. A simple interface has been made so to fix trivial errors in the detection of the plate orientation, which often occur due to lighting artefacts and whole yeast row of columns that failed to grow.

Fun stuff:

Master's Thesis:
Maximum Likehood Agglomerative Clustering for Color Image Segmentation
When programs go wrong... Pretty Images are made