ayout 1 - EMBL Grenoble

More documents

Recommendations

Info

EMBL-EBI The GO Editorial Office Previous and current research The Gene Ontology (GO) project (www.geneontology.org) is a collaborative effort to construct and use ontologies to facilitate the biologically meaningful annotation of genes and their products in a wide variety of organisms. At the EBI, the GO Editorial Office plays a key role in managing the distributed task of developing and maintaining the GO vocabularies, and contributes to a number of other GO project efforts, including documentation, web presence, software testing and user support. The Gene Ontology Consortium (GOC) provides the scientific community with a consistent and robust infrastructure, in the form of biological ontologies, for describing, integrating, and comparing the structures of genetic elements and the functional roles of gene products within and between organisms. The GO ontologies cover three key biological domains that are shared by all organisms: • molecular function defines the tasks performed by individual gene products; examples include aminoacyl-tRNA ligase activity and translation elongation factor activity; Midori Harris PhD 1997, Cornell University, Ithaca, NY. Scientific Curator, Saccharomyces Genome Database, Stanford University, Stanford, CA. GO Editor at EMBL-EBI since 2001. • biological process defines broad biological goals, such as signal transduction or ribosome assembly, that are accomplished by ordered assemblies of molecular functions; • cellular component describes subcellular structures, locations and macromolecular complexes; examples include cytoplasm, ribosome and translation release factor complex. In addition, sequence features are covered by the Sequence Ontology, which is maintained separately from the three GO ontologies (Eilbeck et al., 2005). The ontologies in GO are structured as directed acyclic graphs (DAGs), wherein any term may have one or more parents and zero, one, or more children. Within each vocabulary, terms are defined and parent–child relationships between terms are specified. A child term is a subset of its parent(s). The GO vocabularies have long defined two semantic relationships between parent and child terms: is_a and part_of. The is_a relationship means that a term is a subclass of its parent; part of may mean ‘physically part of ’ (as in the cellular component ontology) or ‘subprocess of ’ (as in the biological process ontology). New relationships representing biological regulation have recently been added, as described below. The figure shows a portion of the GO cellular component DAG. Future projects and goals The GO Editorial Office will continue to work closely with the rest of the GO Consortium and with biological experts to ensure that the ontologies are comprehensive, logically rigorous and biologically accurate. Improvements begun in 2008 on signal transduction, transcription, and other topics will therefore continue in 2009. The new regulates relationships will be used to create the first links between the biological process and molecular function ontologies, with additional types of links to follow. Work on recasting many complex process terms as explicit crossproducts with orthogonal ontologies such as the ChEBI ontology and the cell ontology will also continue. GO terms are organised in directed acyclic graphs (DAGs) – hierarchical structures in which any ‘child’ (more specialised term) can have many ‘parents’ (less specialised terms). For example, the cellular component term chloroplast envelope has two parents, reflecting the fact that it is a part of the chloroplast and a type of envelope. Any gene that is annotated to this term is automatically annotated to both chloroplast and envelope. Some terms and relationships have been omitted for clarity. Selected references The Gene Ontology Consortium (2008). The Gene Ontology (GO) Project in 2008. Nucleic Acids Res., 36, D0-D Eilbeck, K. et al. (2005). The Sequence Ontology: a tool for the unification of genome annotations. Genome Biol., 6, R The Gene Ontology Consortium (2001). Creating the Gene Ontology resource: design and implementation. Genome Res., 11, 125-133 75
EMBL Research at a Glance 2009 Kim Henrick PhD 197, University of Western Australia, Perth. Postdoctoral research at the Polytechnic of North London, Imperial College of Science and Technology, SERC Daresbury Laboratory, Cambridge Centre for Protein Engineering and National Institute for Medical Research. Team leader at EMBL-EBI since 2001. Macromolecular Structure Database Team Previous and current research The Macromolecular Structure Database (MSD; www.ebi.ac.uk/msd) holds detailed knowledge of protein structure and function of biological macromolecules. Access to this information is vital for many different users, for example, the identification of potential targets for therapeutic intervention as well as of lead structures for pharmaceutical use. We uniquely integrate the experimental data derived by 3D cryo-electron microscopy and electron tomography techniques, and derive the molecular biological assemblies of structures held in the PDB. Our aim is to provide integrated data resources that evolve with the needs of structural biologists; for all biologists seeking to understand the structural basis of life, for researchers looking for the causative agents of disease and diagnostic tools and for the pharmaceutical and biotech industries. Through our membership of the Worldwide Protein Data Bank organisation (wwPDB; www.wwpdb.org) we are an equal PDB partner and work closely with the United States (RCSB) and Japanese (PDBj) partners to provide the single international archive for structural data. To reflect this status, we are in the process of migrating to a new name, the Protein Data Bank in Europe (PDBe), as recommended by the MSD Scientific Advisory Board. The PDB archive is growing annually in value, importance and size. The current conservative estimate of the value of the entire PDB archive is in excess of $4.5 billion (just over €3 billion), with the annual research cost involved in elucidating these structures estimated to be $750 million (€530 million). More than 15 different funding agencies worldwide fund the wwPDB centres, generating an estimated total of $9 million (€6.4 million) per year. When these figures are compared, the costs of maintaining the archive represents approximately 1% of the annual research investment. The combined MSD services (providing access to 20 different views of PDB data) deliver 3.6 million hits per month, transferring about 238GB to approximately 53,000 users. In addition, users download around 1.7 million and 4 million files per month from the MSD and PDB FTP sites respectively. This year saw the PDB make the deposition of scientific evidence for a macromolecular structure mandatory (www.wwpdb.org/news.html). From 1 February 2008, structure factor amplitudes/intensities (for crystal structures) and restraints (for NMR structures) are now mandatory for PDB deposition. In accordance with this policy, the PDB ID should be included in publications and authors must agree to release the atomic coordinates and associated experimental data when the article is published. Future projects and goals To continue to meet the goals of the PDB as a critical global scientific resource we must evolve with and anticipate the needs of the scientific community. This includes the five- to ten-year vision to enrich the annotation of entries to include biological function as well as all aspects of the PDB services. We aim to maximise the efficiency and effectiveness of macromolecular structure data handling, and support the scientific community through the development and adoption of common deposition and annotation processes and tools. These shared processes and tools will enable balancing of deposition load across the wwPDB member sites and allow for shared maintenance and updates to the archive and tools in the future. The next deposition and annotation product will be a unified system, which will be used at all deposition sites. It is designed to provide significant reduction in curation time, assure consistency and will be extensible to accommodate hybrids and new structural determination methods. It will also provide users with portable validation tools and ‘table 1’ of their experiment. From July 2009, the MSD/PDBe team will be led by Gerard Kleywegt. Selected references Golovin, A. & Henrick, K. (2008). MSDmotif: Exploring protein sites and motifs. BMC Bioinformatics, 9, Article 312 Haquin, S. et al. (2008) Data management in structural genomics: an overview. Methods Mol Biol., 26, 9-79 Henrick, K. et al. (2008) Remediation of the protein data bank archive. Nucleic Acids Res., 36, D26-D33 Lawson, C.L. et al. (2008). Representation of viruses in the remediated PDB archive. Acta Crystallogr. Sect. D-Biol. Crystallogr., 6, 87-882 Markley, J.L. et al. (2008). BioMagResBank (BMRB) as a partner in the Worldwide Protein Data Bank (wwPDB): new policies affecting biomolecular NMR depositions. J. Biomol. NMR, 0, 153-155 76
Page 2:
European Molecular Biology Laborato
Page 5 and 6:
EMBL Research at a Glance 2009 Fore
Page 8 and 9:
Cell Biology and Biophysics Unit Th
Page 10 and 11:
Cell Biology and Biophysics Unit Se
Page 12 and 13:
Cell Biology and Biophysics Unit Ce
Page 14 and 15:
Cell Biology and Biophysics Unit Ch
Page 16 and 17:
Cell Biology and Biophysics Unit Dy
Page 18 and 19:
Cell Biology and Biophysics Unit Ce
Page 20 and 21:
Cell Biology and Biophysics Unit Ch
Page 22 and 23:
Cell Biology and Biophysics Unit Ph
Page 24 and 25:
Developmental Biology Unit Cell pol
Page 26 and 27: Developmental Biology Unit Timing o
Page 28 and 29: Developmental Biology Unit Developm
Page 30 and 31: Developmental Biology Unit Gene reg
Page 32 and 33: Gene Expression Unit The genome enc
Page 34 and 35: Gene Expression Unit Functional gen
Page 36 and 37: Gene Expression Unit Computational
Page 38 and 39: Gene Expression Unit Studying the o
Page 40 and 41: Gene Expression Unit Chromatin plas
Page 42 and 43: Structural and Computational Biolog
Page 54 and 55: Directors’ Research The RanGTPase
Page 56 and 57: Core Facilities The Core Facilities
Page 58 and 59: Core Facilities Chemical Biology Co
Page 60 and 61: Core Facilities Flow Cytometry Core
Page 62 and 63: Core Facilities Protein Expression
Page 64 and 65: EMBL-EBI, Hinxton, UK The European
Page 66 and 67: EMBL-EBI Differentiation and develo
Page 68 and 69: EMBL-EBI Evolutionary tools for seq
Page 70 and 71: EMBL-EBI Genome-scale analysis of r
Page 72 and 73: EMBL-EBI PANDA proteins and the Apw
Page 74 and 75: EMBL-EBI The Microarray Informatics
Page 78 and 79: EMBL-EBI The Proteomics Services Te
Page 80 and 81: EMBL-EBI Ensembl Genomes Previous a
Page 82 and 83: EMBL-EBI Chemogenomics and drug dis
Page 84 and 85: EMBL-EBI The Microarray Software De
Page 86 and 87: EMBL-EBI Literature resource develo
Page 88 and 89: EMBL Grenoble, France The EMBL outs
Page 90 and 91: EMBL Grenoble Structural biology of
Page 92 and 93: EMBL Grenoble High-throughput prote
Page 94 and 95: EMBL Grenoble Synchrotron Crystallo
Page 96 and 97: EMBL Grenoble Regulation of gene ex
Page 98 and 99: EMBL Hamburg, Germany EMBL Hamburg
Page 100 and 101: EMBL Hamburg Instrumentation for sy
Page 102 and 103: EMBL Hamburg Macromolecular crystal
Page 104 and 105: EMBL Hamburg Disease-related protei
Page 106 and 107: EMBL Hamburg SAXS studies of biolog
Page 108 and 109: EMBL Hamburg X-ray crystallography
Page 110 and 111: EMBL Monterotondo Regenerative mech
Page 112 and 113: EMBL Monterotondo Molecular physiol
Page 114 and 115: EMBL Monterotondo Transcription fac
Page 116 and 117: Notes 115
Page 118 and 119: Notes 117
Page 120 and 121: Ladurner, Andreas 39 L Lamzin, Vict
show all

ayout 1 - EMBL Grenoble

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?