Christian Lemer
Université libre de Bruxelles
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Publication
Featured researches published by Christian Lemer.
Nature Biotechnology | 2010
Emek Demir; Michael P. Cary; Suzanne M. Paley; Ken Fukuda; Christian Lemer; Imre Vastrik; Guanming Wu; Peter D'Eustachio; Carl F. Schaefer; Joanne S. Luciano; Frank Schacherer; Irma Martínez-Flores; Zhenjun Hu; Verónica Jiménez-Jacinto; Geeta Joshi-Tope; Kumaran Kandasamy; Alejandra López-Fuentes; Huaiyu Mi; Elgar Pichler; Igor Rodchenkov; Andrea Splendiani; Sasha Tkachev; Jeremy Zucker; Gopal Gopinath; Harsha Rajasimha; Ranjani Ramakrishnan; Imran Shah; Mustafa Syed; Nadia Anwar; Özgün Babur
Biological Pathway Exchange (BioPAX) is a standard language to represent biological pathways at the molecular and cellular level and to facilitate the exchange of pathway data. The rapid growth of the volume of pathway data has spurred the development of databases and computational tools to aid interpretation; however, use of these data is hampered by the current fragmentation of pathway information across many databases with incompatible formats. BioPAX, which was created through a community process, solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. Using BioPAX, millions of interactions, organized into thousands of pathways, from many organisms are available from a growing number of databases. This large amount of pathway data in a computable form will support visualization, analysis and biological discovery.
Nucleic Acids Research | 2004
Ulrich Güldener; Martin Münsterkötter; Gabi Kastenmüller; N. Strack; J. Van Helden; Christian Lemer; J. Richelles; José García-Martínez; José E. Pérez-Ortín; H. Michael; Andreas Kaps; Emmanuel Talla; Bernard Dujon; Bernard André; Jean-Luc Souciet; J. De Montigny; Elisabeth Bon; Claude Gaillardin; Hans-Werner Mewes
The Comprehensive Yeast Genome Database (CYGD) compiles a comprehensive data resource for information on the cellular functions of the yeast Saccharomyces cerevisiae and related species, chosen as the best understood model organism for eukaryotes. The database serves as a common resource generated by a European consortium, going beyond the provision of sequence information and functional annotations on individual genes and proteins. In addition, it provides information on the physical and functional interactions among proteins as well as other genetic elements. These cellular networks include metabolic and regulatory pathways, signal transduction and transport processes as well as co-regulated gene clusters. As more yeast genomes are published, their annotation becomes greatly facilitated using S.cerevisiae as a reference. CYGD provides a way of exploring related genomes with the aid of the S.cerevisiae genome as a backbone and SIMAP, the Similarity Matrix of Proteins. The comprehensive resource is available under http://mips.gsf.de/genre/proj/yeast/.
Nucleic Acids Research | 2004
Christian Lemer; Erick Antezana; Fabian Couche; Frédéric Fays; Xavier Santolaria; Rekin’s Janky; Yves Deville; Jean Richelle
The aMAZE LightBench (http://www.amaze.ulb. ac.be/) is a web interface to the aMAZE relational database, which contains information on gene expression, catalysed chemical reactions, regulatory interactions, protein assembly, as well as metabolic and signal transduction pathways. It allows the user to browse the information in an intuitive way, which also reflects the underlying data model. Moreover links are provided to literature references, and whenever appropriate, to external databases.
Nature Biotechnology | 2012
Emek Demir; Michael P. Cary; Suzanne M. Paley; Ken Fukuda; Christian Lemer; Imre Vastrik; Guanming Wu; Peter D'Eustachio; Carl F. Schaefer; Joanne S. Luciano; Frank Schacherer; Irma Martínez-Flores; Zhenjun Hu; Verónica Jiménez-Jacinto; Geeta Joshi-Tope; Kumaran Kandasamy; Alejandra López-Fuentes; Huaiyu Mi; Elgar Pichler; Igor Rodchenkov; Andrea Splendiani; Sasha Tkachev; Jeremy Zucker; Gopal Gopinath; Harsha Rajasimha; Ranjani Ramakrishnan; Imran Shah; Mustafa Syed; Nadia Anwar; Özgün Babur
BioPAX (Biological Pathway Exchange) is a standard language to represent biological pathways at the molecular and cellular level. Its major use is to facilitate the exchange of pathway data (http://www.biopax.org). Pathway data captures our understanding of biological processes, but its rapid growth necessitates development of databases and computational tools to aid interpretation. However, the current fragmentation of pathway information across many databases with incompatible formats presents barriers to its effective use. BioPAX solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. BioPAX was created through a community process. Through BioPAX, millions of interactions organized into thousands of pathways across many organisms, from a growing number of sources, are available. Thus, large amounts of pathway data are available in a computable form to support visualization, analysis and biological discovery.
Archive | 2007
Yves Deville; Christian Lemer
Systems biology aims at understanding the holistic behavior of biological systems. A very important step toward this goal is to develop a theoretical framework in which we can embed the detailed knowledge that biologists are accumulating at increasing speed, which will then allow us to compute the outcomes of the complex interplay between the myriad interactions that take place in the system. This chapter deals with important basic aspects of this theoretical framework that lie on the divide between systems biology and bioinformatics. In the first part, it discusses the conceptual models used for representing detailed knowledge on various types of biochemical pathways and interactions. As much of this knowledge deals with the complex networks of functional and physical interactions between the different molecular players, the second part of this chapter reviews the conceptual models and methods used to analyze various properties of these networks.
Proteins | 1995
Christian Lemer; Marianne Rooman
Briefings in Bioinformatics | 2001
Jacques van Helden; Avi Naim; Christian Lemer; Renato Mancuso; Matthew Eldridge; Shoshana J. Wodak
Archive | 2005
Gary D. Bader; Eric Brauner; Michael P. Cary; Kam D. Dahlquist; Emek Demir; Peter D'Eustachio; Ken Fukuda; Frank Gibbons; Marc Gillespie; Robert N. Goldberg; Chris Hogue; Michael Hucka; Geeta Joshi-Tope; David Kane; Peter D. Karp; Teri Klein; Christian Lemer; Joanne S. Luciano; Debbie Marks; Natalia Maltsev; Elizabeth Marland; Eric Neumann; Suzanne M. Paley; Jonathan Rees; Aviv Regev; Alan Ruttenberg; Andrey Rzhetsky; Chris Sander; Imran Shah; Andrea Splendiani
Nature Biotechnology | 2010
Emek Demir; Michael P. Cary; Suzanne M. Paley; Ken Fukuda; Christian Lemer; Imre Vastrik; Guanming Wu; Peter D'Eustachio; Carl F. Schaefer; Joanne S. Luciano; Frank Schacherer; Irma Martínez-Flores; Zhenjun Hu; Verónica Jiménez-Jacinto; Geeta Joshi-Tope; Kumaran Kandasamy; Alejandra López-Fuentes; Huaiyu Mi; Elgar Pichler; Igor Rodchenkov; Andrea Splendiani; Sasha Tkachev; Jeremy Zucker; Gopal Gopinath; Harsha Rajasimha; Ranjani Ramakrishnan; Imran Shah; Mustafa Syed; Nadia Anwar; Özgün Babur
Archive | 2003
Christian Lemer; Erick Antezana; Fabian Couche; Frédéric Fays; Jean Richelle
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National Institute of Advanced Industrial Science and Technology
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