SBML models and MathSBML

MathSBML is an open-source, freely-downloadable Mathematica package that facilitates working with Systems Biology Markup Language (SBML) models. SBML is a toolneutral,computer-readable format for representing models of biochemical reaction networks, applicable to metabolic networks, cell-signaling pathways, genomic regulatory networks, and other modeling problems in systems biology that is widely supported by the systems biology community. SBML is based on XML, a standard medium for representing and transporting data that is widely supported on the internet as well as in computational biology and bioinformatics. Because SBML is tool-independent, it enables model transportability, reuse, publication and survival. In addition to MathSBML, a number of other tools that support SBML model examination and manipulation are provided on the sbml.org website, including libSBML, a C/C++ library for reading SBML models; an SBML Toolbox for MatLab; file conversion programs; an SBML model validator and visualizer; and SBML specifications and schemas. MathSBML enables SBML file import to and export from Mathematica as well as providing an API for model manipulation and simulation

Good Learning and Implicit Model Enumeration

MathSBML is an open-source, freely-downloadable Mathematica package that facilitates working with Systems Biology Markup Language (SBML) models. SBML is a toolneutral,computer-readable format for representing models of biochemical reaction networks, applicable to metabolic networks, cell-signaling pathways, genomic regulatory networks, and other modeling problems in systems biology that is widely supported by the systems biology community. SBML is based on XML, a standard medium for representing and transporting data that is widely supported on the internet as well as in computational biology and bioinformatics. Because SBML is tool-independent, it enables model transportability, reuse, publication and survival. In addition to MathSBML, a number of other tools that support SBML model examination and manipulation are provided on the sbml.org website, including libSBML, a C/C++ library for reading SBML models; an SBML Toolbox for MatLab; file conversion programs; an SBML model validator and visualizer; and SBML specifications and schemas. MathSBML enables SBML file import to and export from Mathematica as well as providing an API for model manipulation and simulation

Using a reduced spot size for intensity-modulated proton therapy potentially improves salivary gland-sparing in oropharyngeal cancer

Purpose: To investigate whether intensity-modulated proton therapy with a reduced spot size (rsIMPT) could further reduce the parotid and submandibular gland dose compared with previously calculated IMPT plans with a larger spot size. In addition, it was investigated whether the obtained dose reductions would theoretically translate into a reduction of normal tissue complication probabilities (NTCPs). Methods: Ten patients with N0 oropharyngeal cancer were included in a comparative treatment planning study. Both IMPT plans delivered simultaneously 70 Gy to the boost planning target volume (PTV) and 54 Gy to the elective nodal PTV. IMPT and rsIMPT used identical three-field beam arrangements. In the IMPT plans, the parotid and submandibular salivary glands were spared as much as possible. rsIMPT plans used identical dose-volume objectives for the parotid glands as those used by the IMPT plans, whereas the objectives for the submandibular glands were tightened further. NTCPs were calculated for salivary dysfunction and xerostomia. Results: Target coverage was similar for both IMPT techniques, whereas rsIMPT clearly improved target conformity. The mean doses in the parotid glands and submandibular glands were significantly lower for three-field rsIMPT (14.7 Gy and 46.9 Gy, respectively) than for three-field IMPT (16.8 Gy and 54.6 Gy, respectively). Hence, rsIMPT significantly reduced the NTCP of patient-rated xerostomia and parotid and contralateral submandibular salivary flow dysfunction (27%, 17%, and 43% respectively) compared with IMPT (39%, 20%, and 79%, respectively). In addition, mean dose values in the sublingual glands, the soft palate and oral cavity were also decreased. Obtained dose and NTCP reductions varied per patient. Conclusions: rsIMPT improved sparing of the salivary glands and reduced NTCP for xerostomia and parotid and submandibular salivary dysfunction, while maintaining similar target coverage results. It is expected that rsIMPT improves quality of life during and after radiotherapy treatment.</p

Identifying Prototypical Components in Behaviour Using Clustering Algorithms

Quantitative analysis of animal behaviour is a requirement to understand the task solving strategies of animals and the underlying control mechanisms. The identification of repeatedly occurring behavioural components is thereby a key element of a structured quantitative description. However, the complexity of most behaviours makes the identification of such behavioural components a challenging problem. We propose an automatic and objective approach for determining and evaluating prototypical behavioural components. Behavioural prototypes are identified using clustering algorithms and finally evaluated with respect to their ability to represent the whole behavioural data set. The prototypes allow for a meaningful segmentation of behavioural sequences. We applied our clustering approach to identify prototypical movements of the head of blowflies during cruising flight. The results confirm the previously established saccadic gaze strategy by the set of prototypes being divided into either predominantly translational or rotational movements, respectively. The prototypes reveal additional details about the saccadic and intersaccadic flight sections that could not be unravelled so far. Successful application of the proposed approach to behavioural data shows its ability to automatically identify prototypical behavioural components within a large and noisy database and to evaluate these with respect to their quality and stability. Hence, this approach might be applied to a broad range of behavioural and neural data obtained from different animals and in different contexts

Proceedings of Abstracts Engineering and Computer Science Research Conference 2019

© 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is © 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care

OREMPdb: a semantic dictionary of computational pathway models

<p>Abstract</p> <p>Background</p> <p>The information coming from biomedical ontologies and computational pathway models is expanding continuously: research communities keep this process up and their advances are generally shared by means of dedicated resources published on the web. In fact, such models are shared to provide the characterization of molecular processes, while biomedical ontologies detail a semantic context to the majority of those pathways. Recent advances in both fields pave the way for a scalable information integration based on aggregate knowledge repositories, but the lack of overall standard formats impedes this progress. Indeed, having different objectives and different abstraction levels, most of these resources "speak" different languages. Semantic web technologies are here explored as a means to address some of these problems.</p> <p>Methods</p> <p>Employing an extensible collection of interpreters, we developed OREMP (Ontology Reasoning Engine for Molecular Pathways), a system that abstracts the information from different resources and combines them together into a coherent ontology. Continuing this effort we present OREMPdb; once different pathways are fed into OREMP, species are linked to the external ontologies referred and to reactions in which they participate. Exploiting these links, the system builds species-sets, which encapsulate species that operate together. Composing all of the reactions together, the system computes all of the reaction paths from-and-to all of the species-sets.</p> <p>Results</p> <p>OREMP has been applied to the curated branch of BioModels (2011/04/15 release) which overall contains 326 models, 9244 reactions, and 5636 species. OREMPdb is the semantic dictionary created as a result, which is made of 7360 species-sets. For each one of these sets, OREMPdb links the original pathway and the link to the original paper where this information first appeared. </p

Pain as a First Manifestation of Paraneoplastic Neuropathies: A Systematic Review and Meta-Analysis.

INTRODUCTION: Paraneoplastic neurological syndromes (PNS) consist of a heterogeneous group of neurological disorders triggered by cancer. The aim of this systematic review is to estimate the reported prevalence of pain in patients with paraneoplastic peripheral neuropathy (PPN). METHODS: A systematic computer-based literature search was conducted on PubMed database. RESULTS: Our search strategy resulted in the identification of 126 articles. After the eligibility assessment, 45 papers met the inclusion criteria. Full clinical and neurophysiological data were further extracted and involved 92 patients with PPN (54.5% males, mean age 60.0 ± 12.2 years). The commonest first manifestation of PPN is sensory loss (67.4%), followed by pain (41.3%), weakness (22.8%), and sensory ataxia (20.7%). In 13.0% of the cases, pain was the sole first manifestation of the PPN. During the course of the PPN, 57.6% of the patients may experience pain secondary to the neuropathy. CONCLUSIONS: Pain is very prevalent within PPN. Pain specialists should be aware of this. Detailed history-taking, full clinical examination, and requesting nerve conduction studies might lead to an earlier diagnosis of an underlying malignancy

Relating Neuronal to Behavioral Performance: Variability of Optomotor Responses in the Blowfly

Behavioral responses of an animal vary even when they are elicited by the same stimulus. This variability is due to stochastic processes within the nervous system and to the changing internal states of the animal. To what extent does the variability of neuronal responses account for the overall variability at the behavioral level? To address this question we evaluate the neuronal variability at the output stage of the blowfly's (Calliphora vicina) visual system by recording from motion-sensitive interneurons mediating head optomotor responses. By means of a simple modelling approach representing the sensory-motor transformation, we predict head movements on the basis of the recorded responses of motion-sensitive neurons and compare the variability of the predicted head movements with that of the observed ones. Large gain changes of optomotor head movements have previously been shown to go along with changes in the animals' activity state. Our modelling approach substantiates that these gain changes are imposed downstream of the motion-sensitive neurons of the visual system. Moreover, since predicted head movements are clearly more reliable than those actually observed, we conclude that substantial variability is introduced downstream of the visual system

Honeybees' Speed Depends on Dorsal as Well as Lateral, Ventral and Frontal Optic Flows

Flying insects use the optic flow to navigate safely in unfamiliar environments, especially by adjusting their speed and their clearance from surrounding objects. It has not yet been established, however, which specific parts of the optical flow field insects use to control their speed. With a view to answering this question, freely flying honeybees were trained to fly along a specially designed tunnel including two successive tapering parts: the first part was tapered in the vertical plane and the second one, in the horizontal plane. The honeybees were found to adjust their speed on the basis of the optic flow they perceived not only in the lateral and ventral parts of their visual field, but also in the dorsal part. More specifically, the honeybees' speed varied monotonically, depending on the minimum cross-section of the tunnel, regardless of whether the narrowing occurred in the horizontal or vertical plane. The honeybees' speed decreased or increased whenever the minimum cross-section decreased or increased. In other words, the larger sum of the two opposite optic flows in the horizontal and vertical planes was kept practically constant thanks to the speed control performed by the honeybees upon encountering a narrowing of the tunnel. The previously described ALIS (“AutopiLot using an Insect-based vision System”) model nicely matches the present behavioral findings. The ALIS model is based on a feedback control scheme that explains how honeybees may keep their speed proportional to the minimum local cross-section of a tunnel, based solely on optic flow processing, without any need for speedometers or rangefinders. The present behavioral findings suggest how flying insects may succeed in adjusting their speed in their complex foraging environments, while at the same time adjusting their distance not only from lateral and ventral objects but also from those located in their dorsal visual field

Robust Models for Optic Flow Coding in Natural Scenes Inspired by Insect Biology

The extraction of accurate self-motion information from the visual world is a difficult problem that has been solved very efficiently by biological organisms utilizing non-linear processing. Previous bio-inspired models for motion detection based on a correlation mechanism have been dogged by issues that arise from their sensitivity to undesired properties of the image, such as contrast, which vary widely between images. Here we present a model with multiple levels of non-linear dynamic adaptive components based directly on the known or suspected responses of neurons within the visual motion pathway of the fly brain. By testing the model under realistic high-dynamic range conditions we show that the addition of these elements makes the motion detection model robust across a large variety of images, velocities and accelerations. Furthermore the performance of the entire system is more than the incremental improvements offered by the individual components, indicating beneficial non-linear interactions between processing stages. The algorithms underlying the model can be implemented in either digital or analog hardware, including neuromorphic analog VLSI, but defy an analytical solution due to their dynamic non-linear operation. The successful application of this algorithm has applications in the development of miniature autonomous systems in defense and civilian roles, including robotics, miniature unmanned aerial vehicles and collision avoidance sensors