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Eukaryotic Linear Motif resource

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Biological databases are libraries of biological sciences, collected from scientific experiments, published literature, high-throughput experiment technology, and computational analysis. They contain information from research areas including genomics , proteomics , metabolomics , microarray gene expression, and phylogenetics . Information contained in biological databases includes gene function, structure, localization (both cellular and chromosomal), clinical effects of mutations as well as similarities of biological sequences and structures.

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17-559: The Eukaryotic Linear Motif (ELM) resource is a computational biology resource (developed at the European Molecular Biology Laboratory (EMBL)) for investigating short linear motifs (SLiMs) in eukaryotic proteins . It is currently the largest collection of linear motif classes with annotated and experimentally validated linear motif instances. Linear motifs are specified as patterns using regular expression rules. These expressions are used in

34-585: A protein structure database is a database that is modeled around the various experimentally determined protein structures . The aim of most protein structure databases is to organize and annotate the protein structures, providing the biological community access to the experimental data in a useful way. Data included in protein structure databases often includes three-dimensional coordinates as well as experimental information, such as unit cell dimensions and angles for x-ray crystallography determined structures. Though most instances, in this case either proteins or

51-636: A host of biological phenomena from the structure of biomolecules and their interaction, to the whole metabolism of organisms and to understanding the evolution of species . This knowledge helps facilitate the fight against diseases, assists in the development of medications , predicting certain genetic diseases and in discovering basic relationships among species in the history of life . Relational database concepts of computer science and Information retrieval concepts of digital libraries are important for understanding biological databases. Biological database design, development, and long-term management

68-503: A specific structure determinations of a protein, also contain sequence information and some databases even provide means for performing sequence based queries, the primary attribute of a structure database is structural information, whereas sequence databases focus on sequence information, and contain no structural information for the majority of entries. Protein structure databases are critical for many efforts in computational biology such as structure based drug design , both in developing

85-434: Is a core area of the discipline of bioinformatics . Data contents include gene sequences, textual descriptions, attributes and ontology classifications, citations, and tabular data. These are often described as semi- structured data , and can be represented as tables, key delimited records, and XML structures. Most biological databases are available through web sites that organise data such that users can browse through

102-639: Is a special yearly issue of the journal Nucleic Acids Research (NAR). The Database Issue of NAR is freely available, and categorizes many of the public biological databases. A companion database to the issue called the Online Molecular Biology Database Collection lists 1,380 online databases. Other collections of databases exist such as MetaBase and the Bioinformatics Links Collection. Protein structure database In biology ,

119-584: Is an E. coli database. Other popular model organism databases include Mouse Genome Informatics for the laboratory mouse , Mus musculus , the Rat Genome Database for Rattus , ZFIN for Danio Rerio (zebrafish), PomBase for the fission yeast Schizosaccharomyces pombe , FlyBase for Drosophila , WormBase for the nematodes Caenorhabditis elegans and Caenorhabditis briggsae , and Xenbase for Xenopus tropicalis and Xenopus laevis frogs. Numerous databases attempt to document

136-588: Is how biological databases cross-reference to other databases with accession numbers to link their related knowledge together (e.g. so that the accession number stays the same even if a species name changes). Redundancy is another problem, as many databases must store the same information, e.g. protein structure databases also contain the sequence of the proteins they cover, their sequence, and their bibliographic information. Species-specific databases are available for some species, mainly those that are often used in research ( model organisms ). For example, EcoCyc

153-735: The SMART / Pfam databases) and structure. In addition, both the known ELM instances and any positionally conserved matches in sequences similar to ELM instance sequences are identified and displayed. Biological database Biological databases can be classified by the kind of data they collect (see below). Broadly, there are molecular databases (for sequences, molecules, etc.), functional databases (for physiology, enzyme activities, phenotypes, ecology etc), taxonomic databases (for species and other taxonomic ranks), images and other media, or specimens (for museum collections etc.) Databases are important tools in assisting scientists to analyze and explain

170-1268: The Catalogue of Life draws from 165 databases as of May 2022. Operational costs of the Catalogue of Life are paid for by the Global Biodiversity Information Facility , the Illinois Natural History Survey , the Naturalis Biodiversity Center , and the Smithsonian Institution . Some biological databases also document geographical distribution of different species. Shuang Dai et al. created a new multi-source database to document spatial/geographical distribution of 1,371 bird species in China, as existing databases had been severely lacking in spatial distribution data for many species. Sources for this new database included books, literature, GPS tracking, and online webpage data. The new database displayed taxonomy, distribution, species info, and data sources for each species. After completion of

187-541: The ELM prediction pipeline which detects putative motif instances in protein sequences. To improve the predictive power, context-based rules and logical filters are being developed and applied to reduce the amount of false positives matches. As of 2010 ELM contained 146 different motifs that annotate more than 1300 experimentally determined instances within proteins. The current version of the ELM server provides filtering by cell compartment, phylogeny, globular domain clash (using

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204-404: The bird spatial distribution database, it was discovered that 61% of known species in China were found to be distributed in regions beyond where they were previously known. Medical databases are a special case of biomedical data resource and can range from bibliographies, such as PubMed , to image databases for the development of AI based diagnostic software. For instance, one such image database

221-611: The computational methods used and in providing a large experimental dataset used by some methods to provide insights about the function of a protein. The Protein Data Bank (PDB) was established in 1971 as the central archive of all experimentally determined protein structure data. Today the PDB is maintained by an international consortia collectively known as the Worldwide Protein Data Bank (wwPDB). The mission of

238-466: The data online. In addition the underlying data is usually available for download in a variety of formats. Biological data comes in many formats. These formats include text, sequence data, protein structure and links. Each of these can be found from certain sources, for example: Biological knowledge is distributed among countless databases. This sometimes makes it difficult to ensure the consistency of information, e.g. when different names are used for

255-755: The diversity of life on earth. A prominent example is the Catalogue of Life , first created in 2001 by Species 2000 and the Integrated Taxonomic Information System. The Catalogue of Life is a collaborative project that aims to document taxonomic categorization of all currently accepted species in the world. The Catalogue of Life provides a consolidated and consistent database for researchers and policymakers to reference. The Catalogue of Life curates up-to-date datasets from other sources such as Conifer Database, ICTV MSL (for viruses), and LepIndex (for butterflies and moths). In total,

272-493: The same species or different data formats. As a consequence, inter-operability is a constant challenge for information exchange. For instance, if a DNA sequence database stores the DNA sequence along the name of a species, a name change of that species may break the links to other databases which may use a different name. Integrative bioinformatics is one field attempting to tackle this problem by providing unified access. One solution

289-563: Was developed with the goal of aiding in the development of wound monitoring algorithms. Over 188 multi-modal image sets were curated from 79 patient visits, consisting of photographs, thermal images, and 3D mesh depth maps. Wound outlines were manually drawn and added to the photo datasets. The database was made publicly available in the form of a program called WoundsDB, downloadable from the Chronic Wound Database website. An important resource for finding biological databases

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