http://precedings.nature.com/tags/sequence Recently posted documents tagged with 'sequence' Nature Publishing Group en Nature Precedings http://precedings.nature.com/images/header_logo.gif http://precedings.nature.com http://dx.doi.org/10.1038/npre.2009.3537.1 The Sequence Ontology is an OBO Foundry ontology that provides categories of sequences and sequence features that are applied to the annotation of genomes. To facilitate interoperability with other domain ontologies and to provide a foundation for automated inference, we provide here an axiom system for the Sequence and Junction categories in first- and second-order predicate logics. http://dx.doi.org/10.1038/npre.2009.3537.1 Mon, 03 Aug 2009 09:40:08 UTC A Formal Ontology of Sequences doi:10.1038/npre.2009.3537.1 2009-08-03 Robert Hoehndorf Nature Precedings 2009-08-03T09:40:08Z Manuscript Genetics & Genomics Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3152.1 Linear motifs are short and evolutionarily variable sequence patterns associated with particular functions often involving post-translational modifications, such as phosphorylation, acetylation, glycosylation, targeting signals for cellular compartments, protein cleavage sites and protein–protein interaction.Experimentally they are often neglected because their short length (4-10 residues long), and the fact that they often reside in disordered regions in proteins makes them difficult to detect. For a similar reason, using the sole regular expression to detect linear motifs matches in sequences has almost no predictive power because they are both statistically insignificant and prone to massive over-prediction.The Eukaryotic Linear Motif resource (ELM – http://elm.eu.org) is a bioinformatics facility for investigating candidate short functional motifs in eukaryotic proteins. The ELM database to date has collected more than 140 motifs and their regular expressions patterns as well as information about their instances of occurrence, distribution, crystal structure, publications, etc.In order to reduce the over-prediction inherent to pattern matching against protein sequences and to discriminate true from false positive motif matches, context-based rules and logical filters are applied. The current version includes cell compartment, phylogeny, globular domain clash filters and the more recent structural filter based on known three-dimensional information that relies on structural information, such as residue solvent accessibility and secondary structure features. This implies that a candidate motif can be excluded from further consideration if the protein resides in the wrong cellular compartment or the motif is buried in the core of a globular domain. By considering additional types of context information, we expect that prediction of functional sites by ELM can be considerably improved. In cases where the user cannot provide relevant context information, we consider providing predictions of contextual information in order to improve the ELM performance. For example, since the ELM motif database has been annotated with biological process GO terms, the system could be prepared for addition of a new context filter using biological process. http://dx.doi.org/10.1038/npre.2009.3152.1 Thu, 23 Apr 2009 17:20:38 UTC The Eukaryotic Linear Motif Resource (ELM): Regulatory Sites in Proteins doi:10.1038/npre.2009.3152.1 2009-04-23 Francesca Diella Nature Precedings 2009-04-23T17:20:38Z Poster Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2007.278.1 Checksum algorithms are used in biological databases for integrity check and identification purposes. CRC64 is the only checksum algorithm already included in Biopython. This work proposes two new implementation of known algorithms (GCG Checksum and SEGUID). There is also an application based on SEGUID: Looking for redundancy between two FASTA files full of protein sequences based only in sequence information, by comparing the SEGUIDs of both files.The code is shown in the manuscript and may be available at Biopython.org. http://dx.doi.org/10.1038/npre.2007.278.1 Thu, 28 Jun 2007 04:48:13 UTC New checksum functions for Biopython doi:10.1038/npre.2007.278.1 2007-06-28 Sebastian Bassi Nature Precedings 2007-06-28T04:48:13Z Presentation Bioinformatics http://creativecommons.org/licenses/by/2.5/