splatPop: simulating population scale single-cell RNA sequencing data

Population-scale single-cell RNA sequencing (scRNA-seq) is now viable, enabling finer resolution functional genomics studies and leading to a rush to adapt bulk methods and develop new single-cell-specific methods to perform these studies. Simulations are useful for developing, testing, and benchmarking methods but current scRNA-seq simulation frameworks do not simulate population-scale data with genetic effects. Here, we present splatPop, a model for flexible, reproducible, and well-documented simulation of population-scale scRNA-seq data with known expression quantitative trait loci. splatPop can also simulate complex batch, cell group, and conditional effects between individuals from different cohorts as well as genetically-driven co-expression.

Towards the development of automated fed-batch cell culture processes at microscale

Aim: To investigate the impact of various feeding strategies on the growth and productivity of a GS-CHO cell line. Methods: Feed additions were conducted at fixed volumes or linked to a marker such as cell growth or metabolism and added as bolus or near-continuously using the automated feeding module of the micro-Matrix (Applikon). Results: The selected feeding regimens supported maximum viable cell densities of up to 1.9 × 107 cells ml−1 and final titers of up to 1.13 g l−1. Differences in growth and titer between feeding strategies were insignificant, with the exception of one feeding strategy. Conclusion: As the more complex feeding strategies did not create an advantage, the selection of a simple feeding strategy such as bolus or continuous addition of feed medium is preferred.

Open Data, Models, and Codes for Vanadium Redox Batch Cell Systems: A Systems Approach Using Zero-Dimensional Models

In this paper, we study, analyze, and validate some important zero-dimensional physics-based models for vanadium redox batch cell (VRBC) systems and formulate an adequate physics-based model that can predict the battery performance accurately. In the model formulation process, a systems approach to multiple parameters estimation has been conducted using VRBC systems at low C-rates (∼C/30). In this batch cell system, the effect of ions' crossover through the membrane is dominant, and therefore, the capacity loss phenomena can be explicitly observed. Paradoxically, this means that using the batch system might be a better approach for identifying a more suitable model describing the effect of ions transport. Next, we propose an efficient systems approach, which enables to help understand the battery performance quickly by estimating all parameters of the battery system. Finally, open source codes, executable files, and experimental data are provided to enable people's access to robust and accurate models and optimizers. In battery simulations, different models and optimizers describing the same systems produce different values of the estimated parameters. Providing an open access platform can accelerate the process to arrive at robust models and optimizers by continuous modification from the users' side.