in more detail later in this chapter (seeClustering in hit discovery). Both methods have tuneable parameters that give the practitioner some control over cluster size: the larger the clusters created, the greater the degree of difference between the molecules in different sets, and the harsher ...
This chapter sets the tone for the book by providing insights into why HSA is necessary. Additionally, it highlights what is contained in each chapter and provides author affiliations and additional background details about each of the authors. View chapter Book 2016, Heterogeneous System ...
v). Values of each gene were normalized to the range of 0-1 within each batch by the MaxAbsScaler function in the scikit-learn package in Python. The processed matrix was used as input for the SCALEX model for downstream differential gene expression analysis. For the human fetal atlas ...
Here we introduce Droplet Hi-C, which uses a commercial microfluidic device for high-throughput, single-cell chromatin conformation profiling in droplets. Using Droplet Hi-C, we mapped the chromatin architecture of the mouse cortex and analyzed gene regulatory programs in major cortical cell types. ...
If you are only interested in validating on the randomly generated simulation dataset, then you can simply run following lines based on the specific dataset type you chose in Step 0.For Homogeneous sets:python validate.py --simulation --only_valid --load_path=./checkpoints/checkpoint_simulation...
Briefly, we quantified the gene enrichment score (SCj(i)) for each cell (i) against one of the four gene sets (Gj) associated with the particular cellular state. This score was calculated as the relative averaged expression (Exp) of Gj in cell i compared with a group of genes (Gjcont...
In addition, many biological data sets will include outliers due to experimental arti- facts. Finally, the data set might incorporate multiple sources of data from different domains (e.g different experimental methods, geno- and phenotypic data, etc.), where the relative relevance for the ...
PyMix is a useful tool for cluster analysis of biological data. Due to the general nature of the framework, PyMix can be applied to a wide range of applications and data sets. Background Clustering and biological data The first step in the analysis of many biological data sets is the dete...
If you are only interested in validating on the randomly generated simulation dataset, then you can simply run following lines based on the specific dataset type you chose inStep 0. ForHomogeneoussets: python validate.py --simulation --only_valid --load_path=./checkpoints/checkpoint_simulation_ho...
Involved in this project, four sets of visibilities were fully utilized: one integrated, and the other three extracted from the simulation of similar SKA configurations. There are several attempts to implement radio astronomy applications on MIC [14–16], which are related to front-end computing ...