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Readings: Building quantitative, three-dimensional atlases of gene expression and morphology at cellular resolution and Informatics Tools for Population-level Movement Dynamics

Series of sections of images through development process
Automated image analysis - measuring shapes automatically, database to show images/measurements
Similar process for MorphoVis - imaging (time-lapse movies of microscopic views of embryos); understanding processes that change shape of embryos, lay plan for adult body formation
Frog embryos - develop outside the body, vertebrates but not mammals,  can see a lot with a low-powered microscope, then can follow individual cells
Defining the cellular mechanism of shape-change of embryos
Convergent extension - going from short and wide to narrow and long (separating butt from head)
Mice, zebrafish - enabled by new tech developments (harder than frogs)
Create website/database for quantitative comparison and visualization of morphogenesis in embryos of diverse species
Focus on one process in different organisms
Neural convergent extension leads to spinal cord development; neural tube formation (medical application: neural tube defects)
Researchers make drawings or do measurements of how things are moving, as documented in movies
Re-simulate it in Processing, cells move differently depending on your data which you can enter into the simulation
Cut out tissues from embryo - it still does convergent extension, forms mini spinal cord
Shows which tissue is generating force for shape change
Are cells rearranging or changing shape?
Not random, but in between random and organized
Cells on the edge die and slough off
Can trace every cell and show where it goes (using acetate, coloring in cells)
Can make a figure showing initial and final arrangement
Intercalation - rearrange ot make a narrower, longer array (they're not changing shape)
Mainly happens in the middle of the tissue
Mediolateral intercalation index - can check on different species, see if they use the same mathematics of rearrangement; quantify degree of rearrangement, adding back another tissue, it changes how cells rearrange
Flourescent labeling - genetically encoded dyes can outline each cell
Inject dye into one cell of 16 cell tissue, it gets mixed up to give a random sampling
To rearrange, cells have to be moving-- how are they doing it, quantify this?
Cells have protrusions that stick out
Can trace cell, show how protrusion retracts and extends in different directions
Can quantify angles of protrusions
Today, every cell can be outlined with flourescent label, overlay distortion diagrams showing which areas have more distortion over time (quantifying would be looking at length/width ratio)
Most biologists do more visual analysis, less measurements (even though they want to be more quantitative)
Organic constant - changing nodes of constant, in pattern that needs to be modeled (viscocity)
Lots of inputable parameters for future modeling of cells and tissues
Can program each cell in tissue to have different parameters, ways of interacting
Trying to get right combination of parameters to model what's in the video
Small set of parameters for now, looking to expand it; hard to know how many properties there really are
Utility to modeling just a few properties
More complex/realistic simulations make for better outreach; reducing it to a single feature lets you look very closely at it
If you're doing visualization with data, you're limited by what people have collected
Next step: modeling cells' interactions; adding constraints to simulate tissue environment
People have looked at molecules (asymmetric expression of adhesion molecules in the cell)
Sub-cellular labels for particular molecules
Molecules that regulate cytoskeleton - actin, microtubules; lots of accessory proteins control actin/microtubules
Form of dynamic anatomy; want to now connect molecules to anatomy
Genes are linear, A --> B --> C
Cells: self-organized, emergent property
Are parameters metadata that you can analyze? - to do that, you need automated analysis of image, rather than grad students spending 6 years counting things
People can see more than computers, but field is working on trying to extract 100 parameters from each cell, automatically
Have to check whether the automatic analysis measured what you wanted to measure
ImageJ software
Have to check and make sure things aren't being left out
Motility - students try automated analysis, always go back to doing it manually, too complicated
Scott Frasier at Caltech, MRI on frog embryos
Sustainability - supporting enough people to get funding? Driving down cost of running it?
NIH - there are some "common good" resources that need to be available
NIH may have some support for data repositories?
Xenbase - Every organism has some database
Choice of tools depends on what can be learned and used easily
Amar: Bioengineering society event; Bioinformatics - invited a bunch of researchers with projects, and students
Students want internships, researchers need manpower
Wanted students with quantitative backgrounds, freshmen/sophomores to work for multiple years
URAP - most people who use it are mechanical or civil engineers, not many other fields
Just showed up at society meeting; not really aware of various directories
Student groups - find meetings, show up
Connect with a professor teaching CS classes, post something on bSpace
Overlap between bioinformatics and art history; did a project using ImageJ to measure forms in abstract art
Amira tracking software - other labs use it, but you have to pay
Hand-compiled reference data sets - testing accuracy of computer measurements?
How much disciplinary discussion is there around standards / being ableto reuse data?
Developmental biology - people are just starting to be quantitative
Increasing discussions about standardizing
Evolution of what funding agencies want
Need more students trained in both quantitative methods & domain
"The Algorithmic Beauty of Plants"


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