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Dive into the research topics where Alice Villéger is active.

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Featured researches published by Alice Villéger.


Nature Biotechnology | 2009

The Systems Biology Graphical Notation

Nicolas Le Novère; Michael Hucka; Huaiyu Mi; Stuart L. Moodie; Falk Schreiber; Anatoly A. Sorokin; Emek Demir; Katja Wegner; Mirit I. Aladjem; Sarala M. Wimalaratne; Frank T. Bergman; Ralph Gauges; Peter Ghazal; Hideya Kawaji; Lu Li; Yukiko Matsuoka; Alice Villéger; Sarah E. Boyd; Laurence Calzone; Mélanie Courtot; Ugur Dogrusoz; Tom C. Freeman; Akira Funahashi; Samik Ghosh; Akiya Jouraku; Sohyoung Kim; Fedor A. Kolpakov; Augustin Luna; Sven Sahle; Esther Schmidt

Circuit diagrams and Unified Modeling Language diagrams are just two examples of standard visual languages that help accelerate work by promoting regularity, removing ambiguity and enabling software tool support for communication of complex information. Ironically, despite having one of the highest ratios of graphical to textual information, biology still lacks standard graphical notations. The recent deluge of biological knowledge makes addressing this deficit a pressing concern. Toward this goal, we present the Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists. SBGN consists of three complementary languages: process diagram, entity relationship diagram and activity flow diagram. Together they enable scientists to represent networks of biochemical interactions in a standard, unambiguous way. We believe that SBGN will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge, from gene regulation, to metabolism, to cellular signaling.


Molecular Systems Biology | 2014

Controlled vocabularies and semantics in systems biology

Mélanie Courtot; Nick Juty; Christian Knüpfer; Dagmar Waltemath; Anna Zhukova; Andreas Dräger; Michel Dumontier; Andrew Finney; Martin Golebiewski; Janna Hastings; Stefan Hoops; Sarah M. Keating; Douglas B. Kell; Samuel Kerrien; James Lawson; Allyson L. Lister; James Lu; Rainer Machné; Pedro Mendes; Matthew Pocock; Nicolas Rodriguez; Alice Villéger; Darren J. Wilkinson; Sarala M. Wimalaratne; Camille Laibe; Michael Hucka; Nicolas Le Novère

The use of computational modeling to describe and analyze biological systems is at the heart of systems biology. Model structures, simulation descriptions and numerical results can be encoded in structured formats, but there is an increasing need to provide an additional semantic layer. Semantic information adds meaning to components of structured descriptions to help identify and interpret them unambiguously. Ontologies are one of the tools frequently used for this purpose. We describe here three ontologies created specifically to address the needs of the systems biology community. The Systems Biology Ontology (SBO) provides semantic information about the model components. The Kinetic Simulation Algorithm Ontology (KiSAO) supplies information about existing algorithms available for the simulation of systems biology models, their characterization and interrelationships. The Terminology for the Description of Dynamics (TEDDY) categorizes dynamical features of the simulation results and general systems behavior. The provision of semantic information extends a models longevity and facilitates its reuse. It provides useful insight into the biology of modeled processes, and may be used to make informed decisions on subsequent simulation experiments.


Bioinformatics | 2012

Software support for SBGN maps

Martijn P. van Iersel; Alice Villéger; Tobias Czauderna; Sarah E. Boyd; Frank Bergmann; Augustin Luna; Emek Demir; Anatoly Sorokin; Ugur Dogrusoz; Yukiko Matsuoka; Akira Funahashi; Mirit I. Aladjem; Huaiyu Mi; Stuart L. Moodie; Hiroaki Kitano; Nicolas Le Novère; Falk Schreiber

Motivation: LibSBGN is a software library for reading, writing and manipulating Systems Biology Graphical Notation (SBGN) maps stored using the recently developed SBGN-ML file format. The library (available in C++ and Java) makes it easy for developers to add SBGN support to their tools, whereas the file format facilitates the exchange of maps between compatible software applications. The library also supports validation of maps, which simplifies the task of ensuring compliance with the detailed SBGN specifications. With this effort we hope to increase the adoption of SBGN in bioinformatics tools, ultimately enabling more researchers to visualize biological knowledge in a precise and unambiguous manner. Availability and implementation: Milestone 2 was released in December 2011. Source code, example files and binaries are freely available under the terms of either the LGPL v2.1+ or Apache v2.0 open source licenses from http://libsbgn.sourceforge.net. Contact: [email protected]


BMC Bioinformatics | 2009

Visualising biological data: A semantic approach to tool and database integration

Steve Pettifer; David Thorne; Philip McDermott; James Marsh; Alice Villéger; Douglas B. Kell; Teresa K. Attwood

MotivationIn the biological sciences, the need to analyse vast amounts of information has become commonplace. Such large-scale analyses often involve drawing together data from a variety of different databases, held remotely on the internet or locally on in-house servers. Supporting these tasks are ad hoc collections of data-manipulation tools, scripting languages and visualisation software, which are often combined in arcane ways to create cumbersome systems that have been customised for a particular purpose, and are consequently not readily adaptable to other uses. For many day-to-day bioinformatics tasks, the sizes of current databases, and the scale of the analyses necessary, now demand increasing levels of automation; nevertheless, the unique experience and intuition of human researchers is still required to interpret the end results in any meaningful biological way. Putting humans in the loop requires tools to support real-time interaction with these vast and complex data-sets. Numerous tools do exist for this purpose, but many do not have optimal interfaces, most are effectively isolated from other tools and databases owing to incompatible data formats, and many have limited real-time performance when applied to realistically large data-sets: much of the users cognitive capacity is therefore focused on controlling the software and manipulating esoteric file formats rather than on performing the research.MethodsTo confront these issues, harnessing expertise in human-computer interaction (HCI), high-performance rendering and distributed systems, and guided by bioinformaticians and end-user biologists, we are building reusable software components that, together, create a toolkit that is both architecturally sound from a computing point of view, and addresses both user and developer requirements. Key to the systems usability is its direct exploitation of semantics, which, crucially, gives individual components knowledge of their own functionality and allows them to interoperate seamlessly, removing many of the existing barriers and bottlenecks from standard bioinformatics tasks.ResultsThe toolkit, named Utopia, is freely available from http://utopia.cs.man.ac.uk/.


Bioinformatics | 2010

Arcadia: a visualization tool for metabolic pathways

Alice Villéger; Stephen Pettifer; Douglas B. Kell

Summary: Arcadia translates text-based descriptions of biological networks (SBML files) into standardized diagrams (SBGN PD maps). Users can view the same model from different perspectives and easily alter the layout to emulate traditional textbook representations. Availability and Implementation: Arcadia is written in C++. The source code is available (along with Mac OS and Windows binaries) under the GPL from http://arcadiapathways.sourceforge.net/ Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.


Learned Publishing | 2011

Ceci n'est pas un hamburger: Modelling and representing the scholarly article

Steve Pettifer; Philip McDermott; James Marsh; David Thorne; Alice Villéger; Terri K. Attwood

Current approaches to publishing scholarly work are falling behind the growing demands of modern readers, who need easy access to the underlying data, as well as the ability to consume content on an ever‐growing variety of electronic devices. The pros and cons of the various formats for representing the scholarly article are hotly contested, but as yet these debates have had little tangible impact on the publishing world where, in spite of its apparent limitations, the PDF remains the dominant form of distribution. We discuss fundamental philosophical differences between a scholarly work and its representation, and describe Utopia Documents, which realizes those differences in software, aiming to resolve many of the current issues in this area.


Journal of Integrative Bioinformatics | 2015

Systems Biology Graphical Notation: Process Description language Level 1 Version 1.3.

Stuart L. Moodie; Nicolas Le Novère; Emek Demir; Huaiyu Mi; Alice Villéger

The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Process Description language represents biological entities and processes between these entities within a network. SBGN PD focuses on the mechanistic description and temporal dependencies of biological interactions and transformations. The nodes (elements) are split into entity nodes describing, e.g., metabolites, proteins, genes and complexes, and process nodes describing, e.g., reactions and associations. The edges (connections) provide descriptions of relationships (or influences) between the nodes, such as consumption, production, stimulation and inhibition. Among all three languages of SBGN, PD is the closest to metabolic and regulatory pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.


Journal of Integrative Bioinformatics | 2015

Systems Biology Graphical Notation: Activity Flow language Level 1 Version 1.2.

Huaiyu Mi; Falk Schreiber; Stuart L. Moodie; Tobias Czauderna; Emek Demir; Robin Haw; Augustin Luna; Nicolas Le Novère; Anatoly A. Sorokin; Alice Villéger

The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Activity Flow language represents the influences of activities among various entities within a network. Unlike SBGN PD and ER that focus on the entities and their relationships with others, SBGN AF puts the emphasis on the functions (or activities) performed by the entities, and their effects to the functions of the same or other entities. The nodes (elements) describe the biological activities of the entities, such as protein kinase activity, binding activity or receptor activity, which can be easily mapped to Gene Ontology molecular function terms. The edges (connections) provide descriptions of relationships (or influences) between the activities, e.g., positive influence and negative influence. Among all three languages of SBGN, AF is the closest to signaling pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.


Journal of Integrative Bioinformatics | 2015

Systems Biology Graphical Notation: Entity Relationship language Level 1 Version 2.

Anatoly A. Sorokin; Nicolas Le Novère; Augustin Luna; Tobias Czauderna; Emek Demir; Robin Haw; Huaiyu Mi; Stuart L. Moodie; Falk Schreiber; Alice Villéger

The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Entity Relationship language (ER) represents biological entities and their interactions and relationships within a network. SBGN ER focuses on all potential relationships between entities without considering temporal aspects. The nodes (elements) describe biological entities, such as proteins and complexes. The edges (connections) provide descriptions of interactions and relationships (or influences), e.g., complex formation, stimulation and inhibition. Among all three languages of SBGN, ER is the closest to protein interaction networks in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.


Nature Precedings | 2009

Systems Biology Graphical Notation: Process Description language Level 1

Stuart L. Moodie; Nicolas Le Novère; Emek Demir; Huaiyu Mi; Alice Villéger

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Emek Demir

Memorial Sloan Kettering Cancer Center

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Huaiyu Mi

University of Southern California

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Augustin Luna

Memorial Sloan Kettering Cancer Center

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Mirit I. Aladjem

National Institutes of Health

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Yukiko Matsuoka

Okinawa Institute of Science and Technology

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