To enable gain-of-function and loss-of-function arrayed CRISPR screens, we generated genome-wide activation (‘T.gonfio’, meaning swelling up) and deletion (‘T.spiezzo’, meaning breaking in two) arrayed libraries for human protein-coding genes using ALPA cloning (Fig. 1e). We used the...
The CUDA toolkit comes with a powerful collection of libraries, meaning you do not need to code your own versions to satisfy many common problems. In this chapter we will examine two of these libraries in detail. Even if your only interest is to learn efficient code, it's worth getting ...
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When genomic data for a particular organism are either unavailable or of insufficient quality,de novosequencing(meaning “from the beginning”) is a method of building or updating thereference genome. Although a whole-genome sample...
Va is the space between, the betweenness, not empty space, not space that separates but space that relates, that holds separate entities and things together in the Unity-that-is-All, the space that is context, giving meaning to things. (Albert Wendt, a Samoan poet and writer who lives in...
In PolyMap, each cell supports thousands of interactions (Figure 2D), meaning that the available screening capacity is mostly defined by the number of antigen-expressing cells that can be individually processed and identified. For studies including tens, hundreds, or more antigens, en masse ...
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Rails enforces “convention over configuration”. This approach provides a pre-configured way of doing things, meaning that you end up writing small blocks of code. This framework provides automated testing, allowing you to ship fully functional code. You can generate code for your models, control...
Operations can be nested to any level, meaning that you can compute exact higher-order derivatives and differentiate functions that are internally making use of differentiation, for applications such as hyperparameter optimization. Encog - An advanced neural network and machine learning framework. Encog...
Each unit implements a nonlinear function of the weighted sum of its inputs; thus, the output of the whole ANN is a composite function, as formally intended in mathematics. The networks of neurons are most often layered and “feed-forward”, meaning that units from any layer only output ...