We explain these cell-line dependent effects by the intrinsic differences in the overall mechanical tension due to the various cytoskeletal elements inside the cell. On the other hand, coupled nuclear and cellular movements of U87 cells were driven by actomyosin contraction. Dynein activity was necessary for nuclear migration of C6 cells but active myosin-II was dispensable. We found that both the actomyosin system and microtubules are involved in the nuclear/cellular movements of both cell lines, but their contributions are cell-/migration-type specific. C6 rat and U87 human glioma cells seeded on fibronectin patterns - thereby forced into a bipolar morphology - displayed oscillatory movements of the nucleus or the whole cell, respectively. In order to shed light on the mechanical processes underlying nuclear movements, we adapted a micro-patterning based assay. Despite of its importance, the mechanism of nuclear migration is still poorly understood in mammalian cells. These movements are involved in a number of fundamental biological processes, such as fertilization, cell division, and embryonic development. Nuclear migration is a general term for the movement of the nucleus towards a specific site in the cell. Julia shows that one can have machine performance without sacrificing human convenience.
#Cellprofiler worm toolbox python source code code#
Abstractions in mathematics are captured as code through another technique from computer science, generic programming. Abstraction, what good computation is really about, recognizes what remains the same after differences are stripped away. Multiple dispatch, a technique from computer science, picks the right algorithm for the right circumstance. Specialization allows for custom treatment. We introduce the Julia programming language and its design - a dance between specialization and abstraction. There are parts of a system for the programmer, and other parts best left untouched as they are built by the experts. One must prototype in one language and then rewrite in another language for speed or deploy- ment, andģ. High-level dynamic programs have to be slow,Ģ. Julia questions notions generally held as “laws of nature” by practitioners of numerical computing:ġ. Our comprehensive siRNA dataset provides a public, freely available resource for further statistical and biological analyses in the high-content, high-throughput siRNA screening field.īridging cultures that have often been distant, Julia combines expertise from the diverse fields of computer science and computational science to create a new approach to numerical computing. This is currently particularly interesting when large-scale parallel datasets are becoming more and more publicly available. Our results show parallel RNAi screening can improve the results of individual screens.
By fitting a PMM model to our data, we found several novel hit genes for most of the pathogens studied. Moreover, PMM is able to estimate a sharedness score that can be used to focus follow-up efforts on generic or specific gene regulators.
PMM allows incorporating siRNA weights that can be assigned according to available information on RNAi quality. We show that PMM gains statistical power for hit detection due to parallel screening.
We propose a Parallel Mixed Model (PMM) approach that simultaneously analyzes several non-identical screens performed with the same RNAi libraries. In order to find statistically significant effector genes for pathogen entry, we systematically analyzed entry pathways in human host cells for eight pathogens using image-based kinome-wide siRNA screens with siRNAs from three vendors. However, the quality of large-scale RNAi screening is often deteriorated by off-targets effects. Large-scale RNAi screening has become an important technology for identifying genes involved in biological processes of interest.