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AbstractDespite decades of intensive search for compounds that modulate the activity of particular protein targets, a large proportion of the human kinome remains as yet undrugged. Effective approaches are therefore required to map the massive space of unexplored compound–kinase interactions for novel and potent activities. Here, we carry out a crowdsourced benchmarking of predictive algorithms for kinase inhibitor potencies across multiple kinase families tested on unpublished bioactivity data. We find the top-performing predictions are based on various models, including kernel learning, gradient boosting and deep learning, and their ensemble leads to a predictive accuracy exceeding that of single-dose kinase activity assays. We design experiments based on the model predictions and identify unexpected activities even for under-studied kinases, thereby accelerating experimental mapping efforts. The open-source prediction algorithms together with the bioactivities between 95 compounds and 295 kinases provide a resource for benchmarking prediction algorithms and for extending the druggable kinome.

The extinction of ecosystems and the mechanisms that support or limit species coexistence have long been studied by scientists. It has been shown that competition and cyclic dominance among species promote species coexistence, such as in the classic Rock-Paper-Scissors (RPS) game. However, individuals’ mobility and the underlying topology that defines the neighbourhood relations between individuals also play an important role in maintaining biodiversity. Typically, square grids are used for simulating such interactions. However, these constrain the individuals’ spatial degrees of freedom. In this work, we investigate the effect of the underlying topology on the RPS dynamics. For that purpose, we considered networks with varying node degree distributions and generated according to different theoretical models. We analyzed the time to the first extinction and the patchiness of the in silico ecosystem over time. In general, we observed a distinct large effect of the network topology on the RPS dynamics. Moreover, leaving regular networks aside, the probability of extinction is very high for some network models due to their inherent long-range connections. On the other hand, spatial arrangements characterized by nearest neighbors interactions have fewer long-range correlations, which is essential for biodiversity., Part of proceedings: ISBN 9783030694791, QC 20230118

"This is an Author's Accepted Manuscript of an article published in Grillo, H., M.M.E. Alemany, A. Ortiz, and B. De Baets. 2019. Possibilistic Compositions and State Functions: Application to the Order Promising Process for Perishables. International Journal of Production Research 57 (22). Informa UK Limited: 7006 31. doi:10.1080/00207543.2019.1574039, available online at: https://www.tandfonline.com/doi/full/10.1080/00207543.2019.1574039", [EN] In this paper, we propose the concepts of the composition of possibilistic variables and state functions. While in conventional compositional data analysis, the interdependent components of a deterministic vector must add up to a specific quantity, we consider such components as possibilistic variables. The concept of state function is intended to describe the state of a dynamic variable over time. If a state function is used to model decay in time, it is called the ageing function. We present a practical implementation of our concepts through the development of a model for a supply chain planning problem, specifically the order promising process for perishables. We use the composition of possibilistic variables to model the existence of different non-homogeneous products in a lot (sub-lots with lack of homogeneity in the product), and the ageing function to establish a shelf life-based pricing policy. To maintain a reasonable complexity and computational efficiency, we propose the procedure to obtain an equivalent interval representation based on alpha -cuts, allowing to include both concepts by means of linear mathematical programming. Practical experiments were conducted based on data of a Spanish supply chain dedicated to pack and distribute oranges and tangerines. The results validated the functionality of both, the compositions of possibilistic variables and ageing functions, showing also a very good performance in terms of the interpretation of a real problem with a good computational performance.