PubMed · 8137072
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G Johnson, E X Wu, S K Hilal. 1994. Optimized phase scrambling for RF phase encoding.. https://doi.org/10.1006/jmrb.1994.1007
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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.
Based on available three-dimensional structures of enzyme-inhibitor complexes, the mechanism of the reaction catalysed by HIV protease is studied using molecular dynamics simulations with molecular mechanics and combined quantum-mechanics/molecular-mechanics potential energy functions. The results support the general acid/general base catalysis mechanism, with Asp25' protonated in the enzyme-substrate complex. In the enzyme-substrate complex, the lytic water molecule binds at a position different from the positions of the hydroxyl groups in various aspartic protease-inhibitor complexes. The carboxyl groups at the active site also adopt a different orientation. However, when the lytic water molecule approaches the scissile peptide, the reaction centre changes gradually to a conformation close to that derived from X-ray diffraction studies of various enzyme-inhibitor complexes. The proton transfer processes can take place only after the lytic water molecule has approached the scissile peptide bond to a certain degree. Qualitatively, the free-energy barrier associated with the nucleophilic attack step, which takes place at physiological pH, is comparable with the acid or base-catalysed reactions of model systems. The structure of the tetrahedral intermediate resulting from the nucleophilic attack step also indicates a straightforward pathway of the next reaction step, i.e. the breaking of the C-N bond.