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1.
Nature ; 604(7907): 635-642, 2022 04.
Artículo en Inglés | MEDLINE | ID: mdl-35478233

RESUMEN

The prosperity and lifestyle of our society are very much governed by achievements in condensed matter physics, chemistry and materials science, because new products for sectors such as energy, the environment, health, mobility and information technology (IT) rely largely on improved or even new materials. Examples include solid-state lighting, touchscreens, batteries, implants, drug delivery and many more. The enormous amount of research data produced every day in these fields represents a gold mine of the twenty-first century. This gold mine is, however, of little value if these data are not comprehensively characterized and made available. How can we refine this feedstock; that is, turn data into knowledge and value? For this, a FAIR (findable, accessible, interoperable and reusable) data infrastructure is a must. Only then can data be readily shared and explored using data analytics and artificial intelligence (AI) methods. Making data 'findable and AI ready' (a forward-looking interpretation of the acronym) will change the way in which science is carried out today. In this Perspective, we discuss how we can prepare to make this happen for the field of materials science.


Asunto(s)
Inteligencia Artificial , Ciencia de los Datos
2.
Addict Biol ; 25(2): e12866, 2020 03.
Artículo en Inglés | MEDLINE | ID: mdl-31859437

RESUMEN

One of the major risk factors for global death and disability is alcohol, tobacco, and illicit drug use. While there is increasing knowledge with respect to individual factors promoting the initiation and maintenance of substance use disorders (SUDs), disease trajectories involved in losing and regaining control over drug intake (ReCoDe) are still not well described. Our newly formed German Collaborative Research Centre (CRC) on ReCoDe has an interdisciplinary approach funded by the German Research Foundation (DFG) with a 12-year perspective. The main goals of our research consortium are (i) to identify triggers and modifying factors that longitudinally modulate the trajectories of losing and regaining control over drug consumption in real life, (ii) to study underlying behavioral, cognitive, and neurobiological mechanisms, and (iii) to implicate mechanism-based interventions. These goals will be achieved by: (i) using mobile health (m-health) tools to longitudinally monitor the effects of triggers (drug cues, stressors, and priming doses) and modify factors (eg, age, gender, physical activity, and cognitive control) on drug consumption patterns in real-life conditions and in animal models of addiction; (ii) the identification and computational modeling of key mechanisms mediating the effects of such triggers and modifying factors on goal-directed, habitual, and compulsive aspects of behavior from human studies and animal models; and (iii) developing and testing interventions that specifically target the underlying mechanisms for regaining control over drug intake.


Asunto(s)
Terapia Conductista/métodos , Investigación Biomédica/métodos , Señales (Psicología) , Trastornos Relacionados con Sustancias/fisiopatología , Trastornos Relacionados con Sustancias/terapia , Telemedicina/métodos , Animales , Conducta Cooperativa , Modelos Animales de Enfermedad , Alemania , Humanos , Recurrencia , Trastornos Relacionados con Sustancias/psicología
3.
Biomed Res Int ; 2014: 624024, 2014.
Artículo en Inglés | MEDLINE | ID: mdl-25032219

RESUMEN

Virtual high-throughput screening (vHTS) is an invaluable method in modern drug discovery. It permits screening large datasets or databases of chemical structures for those structures binding possibly to a drug target. Virtual screening is typically performed by docking code, which often runs sequentially. Processing of huge vHTS datasets can be parallelized by chunking the data because individual docking runs are independent of each other. The goal of this work is to find an optimal splitting maximizing the speedup while considering overhead and available cores on Distributed Computing Infrastructures (DCIs). We have conducted thorough performance studies accounting not only for the runtime of the docking itself, but also for structure preparation. Performance studies were conducted via the workflow-enabled science gateway MoSGrid (Molecular Simulation Grid). As input we used benchmark datasets for protein kinases. Our performance studies show that docking workflows can be made to scale almost linearly up to 500 concurrent processes distributed even over large DCIs, thus accelerating vHTS campaigns significantly.


Asunto(s)
Bases de Datos de Proteínas , Descubrimiento de Drogas/métodos , Simulación del Acoplamiento Molecular/métodos , Inhibidores de Proteínas Quinasas/química , Proteínas Quinasas/química
4.
J Chem Theory Comput ; 10(6): 2232-45, 2014 Jun 10.
Artículo en Inglés | MEDLINE | ID: mdl-26580747

RESUMEN

The MoSGrid portal offers an approach to carry out high-quality molecular simulations on distributed compute infrastructures to scientists with all kinds of background and experience levels. A user-friendly Web interface guarantees the ease-of-use of modern chemical simulation applications well established in the field. The usage of well-defined workflows annotated with metadata largely improves the reproducibility of simulations in the sense of good lab practice. The MoSGrid science gateway supports applications in the domains quantum chemistry (QC), molecular dynamics (MD), and docking. This paper presents the open-source MoSGrid architecture as well as lessons learned from its design.

5.
Nature ; 464(7286): 243-9, 2010 Mar 11.
Artículo en Inglés | MEDLINE | ID: mdl-20190736

RESUMEN

Endocytosis is a complex process fulfilling many cellular and developmental functions. Understanding how it is regulated and integrated with other cellular processes requires a comprehensive analysis of its molecular constituents and general design principles. Here, we developed a new strategy to phenotypically profile the human genome with respect to transferrin (TF) and epidermal growth factor (EGF) endocytosis by combining RNA interference, automated high-resolution confocal microscopy, quantitative multiparametric image analysis and high-performance computing. We identified several novel components of endocytic trafficking, including genes implicated in human diseases. We found that signalling pathways such as Wnt, integrin/cell adhesion, transforming growth factor (TGF)-beta and Notch regulate the endocytic system, and identified new genes involved in cargo sorting to a subset of signalling endosomes. A systems analysis by Bayesian networks further showed that the number, size, concentration of cargo and intracellular position of endosomes are not determined randomly but are subject to specific regulation, thus uncovering novel properties of the endocytic system.


Asunto(s)
Endocitosis/fisiología , Perfilación de la Expresión Génica/métodos , Procesamiento de Imagen Asistido por Computador , Metodologías Computacionales , Endosomas/metabolismo , Factor de Crecimiento Epidérmico/metabolismo , Estudio de Asociación del Genoma Completo , Humanos , Redes y Vías Metabólicas/fisiología , Microscopía Confocal , Fenotipo , Transporte de Proteínas/fisiología , Interferencia de ARN , Transducción de Señal/fisiología , Transferrina/metabolismo
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