Biologically Inspired Near Extinct System Reconstruction

Recovery software system operations from a state of extensive damage without human intervention is a challenging problem as it may need to be based on a different infrastructure from the one that the system was originally designed for and deployed on (i.e., computational and communication devices) and significant reorganization of system functionalities. In this paper, we introduce a bio-inspired approach for reconstructing nearly extinct complex software systems. Our approach is based on encoding a computational DNA (co-DNA) of a system and computational analogues of biological processes to enable the transmission of co-DNA over computational devices and, through it, the transformation of these devices into system cells that can realise chunks of the system functionality, and spread further its reconstruction process

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

From Microbial Communities to Distributed Computing Systems

A distributed biological system can be defined as a system whose components are located in different subpopulations, which communicate and coordinate their actions through interpopulation messages and interactions. We see that distributed systems are pervasive in nature, performing computation across all scales, from microbial communities to a flock of birds. We often observe that information processing within communities exhibits a complexity far greater than any single organism. Synthetic biology is an area of research which aims to design and build synthetic biological machines from biological parts to perform a defined function, in a manner similar to the engineering disciplines. However, the field has reached a bottleneck in the complexity of the genetic networks that we can implement using monocultures, facing constraints from metabolic burden and genetic interference. This makes building distributed biological systems an attractive prospect for synthetic biology that would alleviate these constraints and allow us to expand the applications of our systems into areas including complex biosensing and diagnostic tools, bioprocess control and the monitoring of industrial processes. In this review we will discuss the fundamental limitations we face when engineering functionality with a monoculture, and the key areas where distributed systems can provide an advantage. We cite evidence from natural systems that support arguments in favor of distributed systems to overcome the limitations of monocultures. Following this we conduct a comprehensive overview of the synthetic communities that have been built to date, and the components that have been used. The potential computational capabilities of communities are discussed, along with some of the applications that these will be useful for. We discuss some of the challenges with building co-cultures, including the problem of competitive exclusion and maintenance of desired community composition. Finally, we assess computational frameworks currently available to aide in the design of microbial communities and identify areas where we lack the necessary tool

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

The influence of dopamine on prediction, action and learning

In this thesis I explore functions of the neuromodulator dopamine in the context of autonomous learning and behaviour. I first investigate dopaminergic influence within a simulated agent-based model, demonstrating how modulation of synaptic plasticity can enable reward-mediated learning that is both adaptive and self-limiting. I describe how this mechanism is driven by the dynamics of agentenvironment interaction and consequently suggest roles for both complex spontaneous neuronal activity and specific neuroanatomy in the expression of early, exploratory behaviour. I then show how the observed response of dopamine neurons in the mammalian basal ganglia may also be modelled by similar processes involving dopaminergic neuromodulation and cortical spike-pattern representation within an architecture of counteracting excitatory and inhibitory neural pathways, reflecting gross mammalian neuroanatomy. Significantly, I demonstrate how combined modulation of synaptic plasticity and neuronal excitability enables specific (timely) spike-patterns to be recognised and selectively responded to by efferent neural populations, therefore providing a novel spike-timing based implementation of the hypothetical ‘serial-compound’ representation suggested by temporal difference learning. I subsequently discuss more recent work, focused upon modelling those complex spike-patterns observed in cortex. Here, I describe neural features likely to contribute to the expression of such activity and subsequently present novel simulation software allowing for interactive exploration of these factors, in a more comprehensive neural model that implements both dynamical synapses and dopaminergic neuromodulation. I conclude by describing how the work presented ultimately suggests an integrated theory of autonomous learning, in which direct coupling of agent and environment supports a predictive coding mechanism, bootstrapped in early development by a more fundamental process of trial-and-error learning

Identifying Parameters for Robust Network Growth using Attachment Kernels: A case study on directed and undirected networks

Network growing mechanisms are used to construct random networks that have structural behaviors similar to existing networks such as genetic networks, in efforts of understanding the evolution of complex topologies. Popular mechanisms, such as preferential attachment, are capable of preserving network features such as the degree distribution. However, little is known about such randomly grown structures regarding robustness to disturbances (e.g., edge deletions). Moreover, preferential attachment does not target optimizing the network\u27s functionality, such as information flow. Here, we consider a network to be optimal if it\u27s natural functionality is relatively high in addition to possessing some degree of robustness to disturbances. Specifically, a robust network would continue to (1) transmit information, (2) preserve it\u27s connectivity and (3) preserve internal clusters post failures. In efforts to pinpoint features that would possibly replace or collaborate with the degree of a node as criteria for preferential attachment, we present a case study on both; undirected and directed networks. For undirected networks, we make a case study on wireless sensor networks in which we outline a strategy using Support Vector Regression. For Directed networks, we formulate an Integer Linear Program to gauge the exact transcriptional regulatory network optimal structures, from there on we can identify variations in structural features post optimization

Simulation Intelligence: Towards a New Generation of Scientific Methods

The original "Seven Motifs" set forth a roadmap of essential methods for the field of scientific computing, where a motif is an algorithmic method that captures a pattern of computation and data movement. We present the "Nine Motifs of Simulation Intelligence", a roadmap for the development and integration of the essential algorithms necessary for a merger of scientific computing, scientific simulation, and artificial intelligence. We call this merger simulation intelligence (SI), for short. We argue the motifs of simulation intelligence are interconnected and interdependent, much like the components within the layers of an operating system. Using this metaphor, we explore the nature of each layer of the simulation intelligence operating system stack (SI-stack) and the motifs therein: (1) Multi-physics and multi-scale modeling; (2) Surrogate modeling and emulation; (3) Simulation-based inference; (4) Causal modeling and inference; (5) Agent-based modeling; (6) Probabilistic programming; (7) Differentiable programming; (8) Open-ended optimization; (9) Machine programming. We believe coordinated efforts between motifs offers immense opportunity to accelerate scientific discovery, from solving inverse problems in synthetic biology and climate science, to directing nuclear energy experiments and predicting emergent behavior in socioeconomic settings. We elaborate on each layer of the SI-stack, detailing the state-of-art methods, presenting examples to highlight challenges and opportunities, and advocating for specific ways to advance the motifs and the synergies from their combinations. Advancing and integrating these technologies can enable a robust and efficient hypothesis-simulation-analysis type of scientific method, which we introduce with several use-cases for human-machine teaming and automated science

Proteomics of Poly(ADP-ribose) Polymerases during DNA Replication and Repair

En 2017, Statistique Canada a rapporté qu'un Canadien sur quatre mourra d’un cancer. Chaque jour, nous sommes confrontés à des facteurs environnementaux qui imposent à notre ADN un stress génotoxique. Ce stress peut avoir de graves conséquences au point de menacer notre intégrité génomique, comme les cassures d'ADN double-brin (DSBs). Heureusement, nos cellules ont deux voies principales pour combattre ce type de lésions : la recombinaison homologue (HR) et la Classical Non-Homologous End-Joining (CNHEJ). La voie HR, un type de réparation sans erreur utilisé dans la phase-S du cycle cellulaire, assure une réparation fidèle de la zone endommagée et conserve l'intégrité de l'information génétique. Les individus porteurs de mutations dans les protéines de cette voie, telles que BRCA1 et BCRA2, sont plus susceptibles de développer des cancers du sein et de l'ovaire. Récemment, la clinique a connu une percée majeure dans le traitement du cancer de l'ovaire. Une nouvelle classe de médicaments a été autorisée par la US Food and Drug Administration (FDA) pour traiter les cancers de l'ovaire récurrents qui présentent une HR défective. Ces médicaments inhibent un des acteurs les plus précoces dans la réponse aux dommages à l'ADN (DDR): la PARP-1 (Poly(ADP-ribose) polymerase-1). Lors de l'induction de dommages à l'ADN, la PARP-1 devient fortement activée, conduisant à la production massive de polymères de poly(ADP-ribose) (PAR) générés à partir de l'hydrolyse du nicotinamide adénine dinucléotide. Ce polymère agira comme une plateforme pour recruter des facteurs de réparation de l'ADN au site de réparation. L'application clinique réussie des inhibiteurs de la PARP (PARPi) vient des observations où les mutations ou l'extinction de BRCA1/2 entraînent une diminution de l'activité HR. L'inhibition de la PARP-1 combinée à cette déficience en HR favorise la mort cellulaire, un phénomène appelé létalité synthétique. Trois PARPi sont actuellement autorisés par la FDA et sont utilisés pour le traitement du cancer gynécologique. Malgré l'efficacité thérapeutique de ces inhibiteurs, les mécanismes induisant une régression tumorale ne sont pas complètement compris. Ainsi, il devient extrêmement important de déchiffrer davantage ces mécanismes pour atteindre le plein potentiel des PARPi. Pour ce faire, une recherche fondamentale sur les fonctions des PARPs, et de leurs partenaires dans la DDR, est essentielle et constitue l'objectif général de cette thèse. Durant mon doctorat, nous avons étudié l'influence de la PARP-1 dans la voie HR au moment de l'étape initiale de la résection, qui est essentielle pour l'élimination de l'ADN endommagé. Certaines études ont montré l'implication de la PARP-1 dans le recrutement de la protéine de résection MRE11. Ici, nous démontrons que la PARP-1 a une nouvelle fonction dans la résection des DSBs et nous proposons un nouveau modèle pour expliquer la létalité synthétique observée dans les tumeurs avec une HR défective. Pour compléter l'objectif de ce doctorat, nous avons étudié les rôles régulateurs de la PARP-1 au cours du processus HR, mais plus tard dans la résolution des lésions, c'est-à-dire au maximum de la formation des foyers RAD51, une étape cruciale pour la réparation efficace des DSBs via la HR. Nous avons observé que le PAR-interactome (PARylome) est, à ce moment, fortement enrichi en protéines impliquées dans le métabolisme de l'ARN. Plusieurs des protéines les plus abondantes étaient constituées d’hélicases d’ADN et d’ARN, et de facteurs de transcription. Puisque certains de ces gènes sont mutés dans les tumeurs, ils pourraient théoriquement être des cibles prioritaires pour une utilisation conjointe avec des PARPi. Nous avons également étendu notre étude de la PARylation à la chromatine, au niveau des histones. Nous avons constaté que les queues d'histones ne sont pas les seules cibles de la PARP-1 et que les domaines globulaires centraux sont également PARylés. Finalement, le grand intérêt clinique de la PARP-1 méritait une analyse approfondie de son expression systémique. Ainsi, j'ai terminé mes études en décrivant la distribution et l'abondance tissulaire de la PARP-1 dans les organes simiens, avec l'objectif principal de fournir des informations précieuses quant à l'efficacité potentielle des PARPi ou sa résistance, dans un tissu donné et maladies apparentées. En résumé, cette thèse fournit de nouvelles informations importantes sur les mécanismes orchestrés par la PARP-1 lors de la réponse aux DSBs, y compris les réseaux protéiques complexes engagés dans le remodelage des fonctions cellulaires nécessaire au maintien de l'intégrité génomique.In 2017, Statistics Canada reported that one out of four Canadians will die of cancer. Every day, we face environmental factors that burden our DNA with genotoxic stress. This stress can lead to severe types of DNA damage that can threaten our genomic integrity, namely double-strand breaks (DSBs). Fortunately, our cells have evolved with different repair mechanisms to deal with such lesions. There are two primary types of repair against DSBs: Homologous Recombination (HR) and Classical Non-Homologous End-Joining (CNHEJ). The HR pathway is an error-free repair mechanism used in the S-phase of the cell cycle to ensure faithful repair of the damaged area and thus preserve our genetic information. Individuals that bear mutations in proteins involved in this pathway, such as BRCA1 and BCRA2, have been associated with the development of breast and ovarian cancers. Almost 4 years ago, the field went through a major breakthrough in ovarian cancer care. A new class of drugs was accepted by the US Food and Drug Administration (FDA) to manage recurrent ovarian cancers that display HR-deficiencies. These drugs consist of inhibitor molecules against one of the earliest sensors of DNA damage in the cell: PARP-1 (poly(ADP-ribose) polymerase-1). Upon DNA damage induction, PARP-1 becomes highly activated, leading to the massive production of poly(ADP-ribose) (PAR) polymers, from the hydrolysis of nicotinamide adenine dinucleotide, which in turn modify several proteins posttranslationally and act as a scaffold to recruit DNA repair factors to the repair site. The successful application of PARP inhibitors (PARPi) arose from the observations that mutations or silencing of BRCA1/2, resulted in diminished HR activity. In the context of HR deficiency, the concomitant inhibition of PARP resulted in cell-death, an effect called synthetic lethality. Three PARPi are currently accepted by the FDA and are being clinically used for the treatment of gynaecological cancers. Notwithstanding the great promise of these inhibitors for other types of cancers, the mechanism by which these are inducing cancer lethality is not fully understood. Thus, it becomes of extreme importance to further decipher its mechanistic ways, to achieve full potential of PARPi in the clinic. To achieve this, fundamental research on the functions of PARPs and their protein partners in the DNA damage response is indispensable and constitutes the general aim of this thesis. During my doctoral work, we investigated the influence of PARP-1 during the HR pathway, primarily during the initial step of resection, which is essential for the removal of damaged DNA. Early reports of PARP-1 involvement in resection described the recruitment of the resection protein MRE11 to sites of damage in a PARP-1 dependent manner. Here, we demonstrate that PARP-1 has a novel function in DSB resection and we propose a new model for the synthetic lethality observed in HR-deficient tumors. To further complement the general aim of this doctorate, we investigated the regulatory roles of PARP-1 during the HR pathway, however in a later stage of HR resolution, at the peak formation of RAD51 foci, which is a crucial step for the efficient repair of DSBs through HR. We observed that the PAR-interactome (PARylome) at this stage was abundantly enriched with RNA-processing factors. Several of the most abundant proteins consisted of DNA and RNA helicases, as well as transcription factors, some of which were found to be mutated in tumors, and thus can be seen as potentially druggable targets to be used in combination with PARPi. We also extended our PARylome study to the chromatin proteome and investigated the histone PARylome upon DNA damage. Interestingly, we found that histone tails are not the only targets of PARP-1 and that globular domains are also targets of PARylation. Lastly, the high clinical interest of PARP-1 warrants studies addressing PARP-1 organ distribution. Thus, I finalized my studies by extensively describing and reporting PARP-1 tissular and cellular distribution and abundance in monkey organs, with the main objective of providing valuable information to any study assessing PARP inhibition efficacy and resistance in any given tissue and related diseases. In summary, this thesis provides important new information on the mechanisms PARP-1 is regulating during the response to DSBs, including the networks PARP-1 is orchestrating to potentially help reshape the cell environment, to efficiently repair the most lethal lesion our genome faces

On the psychological origins of tool use

The ubiquity of tool use in human life has generated multiple lines of scientific and philosophical investigation to understand the development and expression of humans' engagement with tools and its relation to other dimensions of human experience. However, existing literature on tool use faces several epistemological challenges in which the same set of questions generate many different answers. At least four critical questions can be identified, which are intimately intertwined-(1) What constitutes tool use? (2) What psychological processes underlie tool use in humans and nonhuman animals? (3) Which of these psychological processes are exclusive to tool use? (4) Which psychological processes involved in tool use are exclusive to Homo sapiens? To help advance a multidisciplinary scientific understanding of tool use, six author groups representing different academic disciplines (e.g., anthropology, psychology, neuroscience) and different theoretical perspectives respond to each of these questions, and then point to the direction of future work on tool use. We find that while there are marked differences among the responses of the respective author groups to each question, there is a surprising degree of agreement about many essential concepts and questions. We believe that this interdisciplinary and intertheoretical discussion will foster a more comprehensive understanding of tool use than any one of these perspectives (or any one of these author groups) would (or could) on their own