PubMed · 8509479
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H J Morowitz. 1993-06-15. The virtual world.. https://doi.org/10.1080/21548331.1993.11442798
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Simulation of realistic omics data is a key input for benchmarking studies that help users obtain optimal computational pipelines. Omics data involves large numbers of measured features on each sample and these measures are generally correlated with each other. However, simulation too often ignores these correlations, perhaps due to computational and statistical hurdles of doing so. To alleviate this, we describe three approaches for generating omics-scale data with correlated measures which mimic real datasets. These approaches are all based on a Gaussian copula approach with a covariance matrix that decomposes into a diagonal part and a low-rank part. This decomposition allows for extremely efficient simulation, overcoming a hurdle for adoption of past methods. We use these approaches to demonstrate the importance of including correlation in two benchmarking applications. First, we show that variance of results from the popular DESeq2 method increases when dependence is included. Second, we demonstrate that CYCLOPS, a method for inferring circadian time of collection from transcriptomics, improves in performance when given gene-gene dependencies in some circumstances. We provide an R package, dependentsimr, that has efficient implementations of these methods and can generate dependent data with arbitrary marginal distributions, including discrete (binary, ordered categorical, Poisson, negative binomial), continuous (normal), or with an empirical distribution.
The goal of cancer immunotherapy is to boost a patient's immune response to a tumour. Yet, the design of an effective immunotherapy is complicated by various factors, including a potentially immunosuppressive tumour microenvironment, immune-modulating effects of conventional treatments and therapy-related toxicities. These complexities can be incorporated into mathematical and computational models of cancer immunotherapy that can then be used to aid in rational therapy design. In this review, we survey modelling approaches under the umbrella of the major challenges facing immunotherapy development, which encompass tumour classification, optimal treatment scheduling and combination therapy design. Although overlapping, each challenge has presented unique opportunities for modellers to make contributions using analytical and numerical analysis of model outcomes, as well as optimization algorithms. We discuss several examples of models that have grown in complexity as more biological information has become available, showcasing how model development is a dynamic process interlinked with the rapid advances in tumour-immune biology. We conclude the review with recommendations for modellers both with respect to methodology and biological direction that might help keep modellers at the forefront of cancer immunotherapy development.
We present here X-ray scattering data that yield new structural information on the multicomponent enzyme methane monooxygenase and its components: a hydroxylase dimer, and two copies each of a reductase and regulatory protein B. Upon formation of the enzyme complex, the hydroxylase undergoes a dramatic conformational change that is observed in the scattering data as a fundamental change in shape of the scattering particle such that one dimension is narrowed (by 25% or 24 A) while the longest dimension increases (by 20% or 25 A). These changes also are reflected in a 13% increase in radius of gyration upon complex formation. Both the reductase and protein B are required for inducing the conformational change. We have modeled the scattering data for the complex by systematically modifying the crystal structure of the hydroxylase and using ellipsoids to represent the reductase and protein B components. Our model indicates that protein B plays a role in optimizing the interaction between the active centers of the reductase and hydroxylase components, thus, facilitating electron transfer between them. In addition, the model suggests reasons why the hydroxylase exists as a dimer and that a possible role for the outlying gamma-subunit may be to stabilize the complex through its interaction with the other components. We further show that proteolysis of protein B to form the inactive B' results in a conformational change and B' does not bind to the hydroxylase. The truncation thus could represent a regulatory mechanism for controlling the enzyme activity.