Progress in Nucleic Acid Research and Molecular Biology: 66

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Reddy ; Brian V.

Progress in nucleic acid research and molecular biology

Battle ; John M. Lawson ; Ardan Patwardhan ; Matthew L. Dianes ; Johannes Griss An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools Manish Sud ; Eoin Fahy ; Dawn Cotter ; Kenan Azam ; Ilango Vadivelu A richer resource for understanding the biochemistry of E. Telukunta ; Anika Erxleben A platform for integrating, standardizing and sharing genome-scale models Zachary A. Bubier ; Timothy Reynolds ; Michael A. Langston ; Elissa J. Forster ; Hilary P. Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database Geoffrey L.

Winsor ; Emma J. Griffiths ; Raymond Lo ; Bhavjinder K. Dhillon ; Julie A. Peabody ; Matthew R. Sheppard ; Benjamin C.

Volume 44 Issue D1 | Nucleic Acids Research | Oxford Academic

Hitz ; Stacia R. Engel ; Giltae Song ; Rama Balakrishnan Speir ; Ann S. Zweig ; Kate R. Rosenbloom ; Brian J. Raney ; Benedict Paten Sloan ; Esther T.


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Amy Tang ; Nuno A. Fonseca ; Elisabet Barrera Howe ; Bruce J. Herndon ; David H. Hall ; Zhuo Du Goodman ; Gillian H. Millburn ; Giulia Antonazzo Elsik ; Aditi Tayal ; Colin M. Diesh ; Deepak R. Unni ; Marianne L. Increased knowing of nucleic acids and their function in molecular biology will additional the various organic sciences together with genetics, biochemistry, and telephone biology.

Progress in Nucleic Acid examine and Molecular Biology presents a discussion board for dialogue of recent discoveries, techniques, and concepts in molecular biology. It includes contributions from leaders of their fields and considerable references. Molecular Biology Problem Solver: Such a lot examine within the existence sciences consists of a center set of molecular-based gear and strategies, for which there's no scarcity of step by step protocols. Molecular Biology challenge Solver: Similarly, the detailed view is retrieved through the accession number link see Figure 1.

For the graphical views, a mouse-over displays the actual positions of the matches on the sequence. Illustration of the detailed view for protein Q, the human protein-tyrosine phosphatase, non-receptor type The oval shapes at the top of the figure display the InterPro Domain Architecture IDA view for this protein, which represents its domain composition.

Each oval shape contains the domain name and the number of its iterations of the domain if greater than one. The InterPro detailed view represents the protein sequence as a series of different lines for each protein signature hit. The bars are colour coded according to the member database. This view provides a complete picture of the protein domain composition and where sequence-based domains correspond to known structures.

This shows where the protein signatures correspond with structural chains. The InterPro Domain Architecture IDA viewer is a graphical representation of protein domain architecture, where the domain architecture of a protein sequence is displayed as a series of non-overlapping domains see Figure 1.


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If two domains overlap slightly, their centres are used to order the domains, and domain boundaries are discarded to enhance a comparison of various architectures. For each InterPro entry, a graphical representation of unique IDA s is provided and each kind of IDA is displayed with an example protein and total number of proteins, sharing this architecture, next to it.

INTRODUCTION

Clicking on the count of proteins retrieves all proteins sharing a common architecture. Although domains should not overlap, inserted domains e. This is represented as a circular display with the taxonomy-tree root as its centre. The lineages populating the nodes were selected to provide a view of the major groups of organisms with the model organisms on the outer most circle.

Nodes of the taxonomy-tree are placed on the inner circles and radial lines lead to the description for each node. No significance is attached to the position of the node on a particular inner-circle, although some attempt has been made to group nodes. The nodes themselves are either true taxonomy nodes or artificial nodes, of which there are three: The number of sequences associated with each lineage is displayed, and clicking the number retrieves the graphical overview for proteins within that taxonomic group.

The bioinorganic motif database, COMe, is an attempt to classify metalloproteins and some other complex proteins using the concept of bioinorganic motifs. These may include the full chain or region s of chain s. The links to the curated structural domains in this field of InterPro entries are based on the correspondence between the proteins matching the InterPro entry and those proteins of known structure belonging to SCOP or CATH superfamilies.

In addition, they include only those links where the structural domains overlap considerably with one or more of the InterPro signatures on the protein sequence. The structural domains are also displayed at the protein level in the graphical views, as described above. This is a useful tool, quite unique in its nature, to show such relationships in a compact way. PIRSF is a network classification system that accommodates a flexible number of levels from superfamily to subfamily to reflect varying degrees of sequence conservation.

Members of a PIRSF homeomorphic family share full-length sequence similarity with a common domain architecture homeomorphic and have common evolutionary origin monophyletic.

Classification based on full-length proteins allows annotation of both generic biochemical and specific biological functions, identification of domain and family relationships, and classification of multidomain proteins. This facilitates comparison of protein families based on structure and sequence and adds a new dimension to InterPro entries. InterPro has a number of applications and databases dependent on its continued success.

It is the tool of choice for the annotation of new genomes and is used extensively for the automatic annotation of TrEMBL entries. This accounts for the bulk of the UniProt proteins that are mapped to GO terms. In addition, InterPro is used for the Proteome Analysis Database 16 , to provide statistical analyses of whole proteomes for the completely sequenced genomes.