Developmental dynamics of transcription and genome architecture

Abstract Regulation of gene expression is necessary for the control of complex developmental processes. The genome has to shape in specific conformations to fit inside the nucleus and to tether specific regulatory elements to their target genes. Although the linear composition of many genomes is largely known, their three dimensional (3D) organization and dynamics are largely unknown. Hence, in order to unravel gene regulation, it is necessary to understand the chromatin structure and organization. Furthermore, developmental procedures are controlled by complex combinatorial transcription factor (TF) networks. Hence, unveiling those networks will provide a better insight towards understanding those developmental procedures. The work described in this thesis aims to study the genome conformation/interactome and their effect on gene regulation and to unveil the role of transcription factor proteins (TFs) in complex developmental processes

SIGMA: Scala Internal Domain-Specific Languages for Model Manipulations

International audienceModel manipulation environments automate model operations such as model consistency checking and model transformation. A number of external model manipulation Domain-Specific Languages (DSL) have been proposed, in particular for the Eclipse Modeling Framework (EMF). While their higher levels of abstraction result in gains in expressiveness over general-purpose languages, their limitations in versatility, performance, and tool support together with the need to learn new languages may significantly contribute to accidental complexities. In this paper, we present Sigma, a family of internal DSLs embedded in Scala for EMF model consistency checking, model-to-model and model-to-text transformations. It combines the benefits of external model manipulation DSLs with general-purpose programming taking full advantage of Scala versatility, performance and tool support. The DSLs are compared to the state-of-the-art Epsilon languages in non-trivial model manipulation tasks that resulted in 20% to 70% reduction in code size and significantly better performance

Comparative efficacy and safety of targeted therapies for BRAF-mutant unresectable or metastatic melanoma: Results from a systematic literature review and a network meta-analysis

Background: The objective of this study was to estimate the relative efficacy and safety of targeted therapies for the treatment of metastatic melanoma using a network meta-analysis (NMA). Methods: A systematic literature review (SLR) identified studies in Medline, Embase and Cochrane published until November 2020. Screening used prespecified eligibility criteria. Following a transitivity assessment across included studies, Bayesian NMA was conducted. Results: A total of 43 publications reporting 15 targeted therapy trials and 42 reporting 18 immunotherapy trials were retained from the SLR and considered for the NMA. Due to substantial between-study heterogeneity with immunotherapy trials, the analysis considered a network restricted to targeted therapies. Among combination therapies, encorafenib + binimetinib was superior to dabrafenib + trametinib for overall response rate (OR = 1.86; 95 % credible interval [CrI] 1.10, 3.17), superior to vemurafenib + cobimetinib with fewer serious adverse events (SAEs) (OR = 0.51; 95 % CrI 0.29, 0.91) and fewer discontinuations due to AEs (OR = 0.45; 95 % CrI 0.21, 0.96), and superior to atezolizumab + vemurafenib + cobimetinib with fewer SAEs (OR = 0.41; 95 % CrI 0.21, 0.82). Atezolizumab + vemurafenib + cobimetinib and encorafenib + binimetinib were generally comparable for efficacy endpoints. Among double combination therapies, encorafenib + binimetinib showed high probabilities of being better for all efficacy and safety endpoints. Conclusions: This NMA confirms that combination therapies are more efficacious than monotherapies. Encorafenib + binimetinib has a favourable efficacy profile compared to other double combination therapies and a favourable safety profile compared to both double and triple combination therapies

Stress-testing centralised model stores

One of the current challenges in model-driven engineering is enabling effective collaborative modelling. Two common approaches are either storing the models in a central repository, or keeping them under a traditional file-based version control system and build a centralized index for model-wide queries. Either way, special attention must be paid to the nature of these repositories and indexes as networked services: they should remain responsive even with an increasing number of concurrent clients. This paper presents an empirical study on the impact of certain key decisions on the scalability of concurrent model queries, using an Eclipse Connected Data Objects model repository and a Hawk model index. The study evaluates the impact of the network protocol, the API design and the internal caching mechanisms and analyzes the reasons for their varying performance

Transient cavitation and friction-induced heating effects of diesel fuel during the needle valve early opening stages for discharge pressures up to 450 mpa

An investigation of the fuel heating, vapor formation, and cavitation erosion location patterns inside a five-hole common rail diesel fuel injector, occurring during the early opening period of the needle valve (from 2 µm to 80 µm), discharging at pressures of up to 450 MPa, is presented. Numerical simulations were performed using the explicit density-based solver of the compressible Navier–Stokes (NS) and energy conservation equations. The flow solver was combined with tabulated property data for a four-component diesel fuel surrogate, derived from the perturbed chain statistical associating fluid theory (PC-SAFT) equation of state (EoS), which allowed for a significant amount of the fuel’s physical and transport properties to be quantified. The Wall Adapting Local Eddy viscosity (WALE) Large Eddy Simulation (LES) model was used to resolve sub-grid scale turbulence, while a cell-based mesh deformation arbitrary Lagrangian–Eulerian (ALE) formulation was used for modelling the injector’s needle valve movement. Friction-induced heating was found to increase significantly when decreasing the pressure. At the same time, the Joule–Thomson cooling effect was calculated for up to 25 degrees K for the local fuel temperature drop relative to the fuel’s feed temperature. The extreme injection pressures induced fuel jet velocities in the order of 1100 m/s, affecting the formation of coherent vortical flow structures into the nozzle’s sac volume

Type inference in flexible model-driven engineering using classification algorithms

Flexible or bottom-up model-driven engineering (MDE) is an emerging approach to domain and systems modelling. Domain experts, who have detailed domain knowledge, typically lack the technical expertise to transfer this knowledge using traditional MDE tools. Flexible MDE approaches tackle this challenge by promoting the use of simple drawing tools to increase the involvement of domain experts in the language definition process. In such approaches, no metamodel is created upfront, but instead the process starts with the definition of example models that will be used to infer the metamodel. Pre-defined metamodels created by MDE experts may miss important concepts of the domain and thus restrict their expressiveness. However, the lack of a metamodel, that encodes the semantics of conforming models has some drawbacks, among others that of having models with elements that are unintentionally left untyped. In this paper, we propose the use of classification algorithms to help with the inference of such untyped elements. We evaluate the proposed approach in a number of random generated example models from various domains. The correct type prediction varies from 23 to 100% depending on the domain, the proportion of elements that were left untyped and the prediction algorithm used

Domain-specific textual meta-modelling languages for model driven engineering

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-31491-9_20Proceedings of 8th European Conference, ECMFA 2012, Kgs. Lyngby, Denmark, July 2-5, 2012Domain-specific modelling languages are normally defined through general-purpose meta-modelling languages like the MOF. While this is satisfactory for many Model-Driven Engineering (MDE) projects, several researchers have identified the need for domain-specific meta-modelling (DSMM) languages providing customised meta-modelling primitives aimed at the definition of modelling languages in a specific domain, as well as the construction of meta-model families. In this paper, we discuss the potential of multi-level meta-modelling for the systematic engineering of DSMM architectures. For this purpose, we present: (i) several primitives and techniques to control the meta-modelling facilities offered to the users of the DSMM languages, (ii) a flexible approach to define textual concrete syntaxes for DSMM languages, (iii) extensions to model management languages enabling the practical use of DSMM in MDE, and (iv) an implementation of these ideas in the metaDepth tool.This work was funded by the Spanish Ministry of Economy and Competitivity (project “Go Lite” TIN2011-24139) and the R&D programme of the Madrid Region (project “e-Madrid” S2009/TIC-1650

Model-based tool support for Tactical Data Links: an experience report from the defence domain

The Tactical Data Link (TDL) allows the exchange of information between cooperating platforms as part of an integrated command and control (C2) system. Information exchange is facilitated by adherence to a complex, message-based protocol defined by document-centric standards. In this paper, we report on a recent body of work investigating migration from a document-centric to a model-centric approach within the context of the TDL domain, motivated by a desire to achieve a positive return on investment. The model-centric approach makes use of the Epsilon technology stack and provides a significant improvement to both the level of abstraction and rigour of the network design. It is checkable by a machine and, by virtue of an MDA-like approach to the separation of domains and model transformation between domains, is open to integration with other models to support more complex workflows, such as by providing the results of interoperability analyses in human-readable domain-specific reports conforming to an accepted standard

Quantum gate algorithm for reference-guided DNA sequence alignment

Reference-guided DNA sequencing and alignment is an important process in computational molecular biology. The amount of DNA data grows very fast, and many new genomes are waiting to be sequenced while millions of private genomes need to be re-sequenced. Each human genome has 3.2 B base pairs, and each one could be stored with 2 bits of information, so one human genome would take 6.4 B bits or about 760 MB of storage (National Institute of General Medical Sciences). Today most powerful tensor processing units cannot handle the volume of DNA data necessitating a major leap in computing power. It is, therefore, important to investigate the usefulness of quantum computers in genomic data analysis, especially in DNA sequence alignment. Quantum computers are expected to be involved in DNA sequencing, initially as parts of classical systems, acting as quantum accelerators. The number of available qubits is increasing annually, and future quantum computers could conduct DNA sequencing, taking the place of classical computing systems. We present a novel quantum algorithm for reference-guided DNA sequence alignment modeled with gate-based quantum computing. The algorithm is scalable, can be integrated into existing classical DNA sequencing systems and is intentionally structured to limit computational errors. The quantum algorithm has been tested using the quantum processing units and simulators provided by IBM Quantum, and its correctness has been confirmed.Comment: 19 pages, 13 figure

Preferential cavitation and friction-induced heating of multi-component Diesel fuel surrogates up to 450MPa

The present work investigates the formation and development of cavitation of a multicomponent Diesel fuel surrogate discharging from a high-pressure fuel injector operating in the range of injection pressures from 60MPa to 450MPa. The compressible form of the Navier-Stokes equations is numerically solved with a density-based solver employing the homogeneous mixture model for accounting the presence of liquid and vapour phases, while turbulence is resolved using a Large Eddy Simulation approximation. Simulations are performed on a tapered heavy-duty Diesel engine injector at a nominal fully-open needle valve lift of 350μm. To account for the effect of extreme fuel pressurisation, two approaches have been followed: (i) a barotropic evolution of density as function of pressure, where thermal effects are not considered and (ii) the inclusion of wall friction-induced and pressurisation thermal effects by solving the energy conservation equation. The PC-SAFT equation of state is utilised to derive thermodynamic property tables for an eight-component surrogate based on a grade no.2 Diesel emissions-certification fuel as function of pressure, temperature, and fuel vapour volume fraction. Moreover, the preferential cavitation of the fuel components within the injector’s hole is predicted by Vapour-Liquid Equilibrium calculations; lighter fuel components are found to cavitate to a greater extent than heavier ones. Results indicate a significant increase of temperature with increasing pressures due to friction-induced heating, leading to a significant increase in the mean vapour pressure of the fuel and an increase of the mass of fuel cavitating, but at the same time to an unprecedented decrease of cavitation volume inside the fuel injector with increasing injection pressure. This has been attributed to the shift of the pressure drop from the feed to the back pressure inside the injection hole orifice as fuel discharges; as injection pressure increases, so does the pressure inside the orifice, confining the location of cavitation formation to a smaller volume attached to the upper part of orifice, thus restricting cavitation growth