A cloud-based enhanced differential evolution algorithm for parameter estimation problems in computational systems biology

This is a post-peer-review, pre-copyedit version of an article published in Cluster Computing. The final authenticated version is available online at: https://doi.org/10.1007/s10586-017-0860-1[Abstract] Metaheuristics are gaining increasing recognition in many research areas, computational systems biology among them. Recent advances in metaheuristics can be helpful in locating the vicinity of the global solution in reasonable computation times, with Differential Evolution (DE) being one of the most popular methods. However, for most realistic applications, DE still requires excessive computation times. With the advent of Cloud Computing effortless access to large number of distributed resources has become more feasible, and new distributed frameworks, like Spark, have been developed to deal with large scale computations on commodity clusters and cloud resources. In this paper we propose a parallel implementation of an enhanced DE using Spark. The proposal drastically reduces the execution time, by means of including a selected local search and exploiting the available distributed resources. The performance of the proposal has been thoroughly assessed using challenging parameter estimation problems from the domain of computational systems biology. Two different platforms have been used for the evaluation, a local cluster and the Microsoft Azure public cloud. Additionally, it has been also compared with other parallel approaches, another cloud-based solution (a MapReduce implementation) and a traditional HPC solution (a MPI implementation)Ministerio de Economía y Competitividad; DPI2014-55276-C5-2-RMinisterio de Economía y Competitividad; TIN2013-42148-PMinisterio de Economía y Competitividad; TIN2016-75845-PXunta de Galicia ; R2016/045Xunta de Galicia; GRC2013/05

How variation in head pitch could affect image matching algorithms for ant navigation

Desert ants are a model system for animal navigation, using visual memory to follow long routes across both sparse and cluttered environments. Most accounts of this behaviour assume retinotopic image matching, e.g. recovering heading direction by finding a minimum in the image difference function as the viewpoint rotates. But most models neglect the potential image distortion that could result from unstable head motion. We report that for ants running across a short section of natural substrate, the head pitch varies substantially: by over 20 degrees with no load; and 60 degrees when carrying a large food item. There is no evidence of head stabilisation. Using a realistic simulation of the ant’s visual world, we demonstrate that this range of head pitch significantly degrades image matching. The effect of pitch variation can be ameliorated by a memory bank of densely sampled along a route so that an image sufficiently similar in pitch and location is available for comparison. However, with large pitch disturbance, inappropriate memories sampled at distant locations are often recalled and navigation along a route can be adversely affected. Ignoring images obtained at extreme pitches, or averaging images over several pitches, does not significantly improve performance

Phototrophic purple bacteria as optoacoustic in vivo reporters of macrophage activity.

The morphology, physiology and immunology, of solid tumors exhibit spatial heterogeneity which complicates our understanding of cancer progression and therapy response. Understanding spatial heterogeneity necessitates high resolution in vivo imaging of anatomical and pathophysiological tumor information. We introduce Rhodobacter as bacterial reporter for multispectral optoacoustic (photoacoustic) tomography (MSOT). We show that endogenous bacteriochlorophyll a in Rhodobacter gives rise to strong optoacoustic signals >800 nm away from interfering endogenous absorbers. Importantly, our results suggest that changes in the spectral signature of Rhodobacter which depend on macrophage activity inside the tumor can be used to reveal heterogeneity of the tumor microenvironment. Employing non-invasive high resolution MSOT in longitudinal studies we show spatiotemporal changes of Rhodobacter spectral profiles in mice bearing 4T1 and CT26.WT tumor models. Accessibility of Rhodobacter to genetic modification and thus to sensory and therapeutic functions suggests potential for a theranostic platform organism