List of Top Disciplines of Database: the Journal of Biological Databases and Curation sorted by citations.

List of Top Schools of Database: the Journal of Biological Databases and Curation sorted by citations.

User-contributed list of biological databases available on the internet. Currently there are 1,801 entries, each describing a different database. The databases are described in a semi-structured way by using templates and entries can carry various user comments and annotations. Entries can be searched, listed or browsed by category. The site uses the same MediaWiki technology that powers Wikipedia, The Mediawiki system allows users to participate on many different levels, ranging from authors and editors to curators and designers. MetaBase aims to be a flexible, user-driven (user-created) resource for the biological database community. The main focuses of MetaBase are: * As a basic requirement, MB contains a list of databases, URLs and descriptions of the most commonly used biological databases currently available on the internet. * The system should be flexible, allowing users to contribute, update and maintain the data in different ways. * In the future we aim to generate more communication between the database developer and user communities.

Developments in sequencing technologies and the sequencing of an ever-increasing number of genomes have revolutionised studies of biodiversity and organismal evolution. This accumulation of data has been paralleled by the creation of numerous public biological databases through which the scientific community can mine the sequences and annotations of genomes, transcriptomes, and proteomes of multiple species. However, to find the appropriate databases and bioinformatic tools for respective inquiries and aims can be challenging. Here, we present a compilation of DNA and protein databases, as well as bioinformatic tools for phylogenetic reconstruction and a wide range of studies on molecular evolution. We provide a protocol for information extraction from biological databases and simple phylogenetic reconstruction using probabilistic and distance methods, facilitating the study of biodiversity and evolution at the molecular level for the broad scientific community.

User-contributed list of biological databases available on the internet. Currently there are 1,801 entries, each describing a different database. The databases are described in a semi-structured way by using templates and entries can carry various user comments and annotations. Entries can be searched, listed or browsed by category. The site uses the same MediaWiki technology that powers Wikipedia, The Mediawiki system allows users to participate on many different levels, ranging from authors and editors to curators and designers. MetaBase aims to be a flexible, user-driven (user-created) resource for the biological database community. The main focuses of MetaBase are: * As a basic requirement, MB contains a list of databases, URLs and descriptions of the most commonly used biological databases currently available on the internet. * The system should be flexible, allowing users to contribute, update and maintain the data in different ways. * In the future we aim to generate more communication between the database developer and user communities.

List of Top Authors of Database: the Journal of Biological Databases and Curation sorted by article citations.

List of NAR Online Molecular Biology Database Collection resources that utilize PDB data (July 2018)

Developments in sequencing technologies and the sequencing of an ever-increasing number of genomes have revolutionised studies of biodiversity and organismal evolution. This accumulation of data has been paralleled by the creation of numerous public biological databases through which the scientific community can mine the sequences and annotations of genomes, transcriptomes, and proteomes of multiple species. However, to find the appropriate databases and bioinformatic tools for respective inquiries and aims can be challenging. Here, we present a compilation of DNA and protein databases, as well as bioinformatic tools for phylogenetic reconstruction and a wide range of studies on molecular evolution. We provide a protocol for information extraction from biological databases and simple phylogenetic reconstruction using probabilistic and distance methods, facilitating the study of biodiversity and evolution at the molecular level for the broad scientific community.

Database of three-dimensional structures of macromolecules that allows the user to retrieve structures for specific molecule types as well as structures for genes and proteins of interest. Three main databases comprise Structure-The Molecular Modeling Database; Conserved Domains and Protein Classification; and the BioSystems Database. Structure also links to the PubChem databases to connect biological activity data to the macromolecular structures. Users can locate structural templates for proteins and interactively view structures and sequence data to closely examine sequence-structure relationships. * Macromolecular structures: The three-dimensional structures of biomolecules provide a wealth of information on their biological function and evolutionary relationships. The Molecular Modeling Database (MMDB), as part of the Entrez system, facilitates access to structure data by connecting them with associated literature, protein and nucleic acid sequences, chemicals, biomolecular interactions, and more. It is possible, for example, to find 3D structures for homologs of a protein of interest by following the Related Structure link in an Entrez Protein sequence record. * Conserved domains and protein classification: Conserved domains are functional units within a protein that act as building blocks in molecular evolution and recombine in various arrangements to make proteins with different functions. The Conserved Domain Database (CDD) brings together several collections of multiple sequence alignments representing conserved domains, in addition to NCBI-curated domains that use 3D-structure information explicitly to define domain boundaries and provide insights into sequence/structure/function relationships. * Small molecules and their biological activity: The PubChem project provides information on the biological activities of small molecules and is a component of NIH''''s Molecular Libraries Roadmap Initiative. PubChem includes three databases: PCSubstance, PCBioAssay, and PCCompound. The PubChem data are linked to other data types (illustrated example) in the Entrez system, making it possible, for example, to retrieve information about a compound and then Link to its biological activity data, retrieve 3D protein structures bound to the compound and interactively view their active sites, and find biosystems that include the compound as a component. * Biological Systems: A biosystem, or biological system, is a group of molecules that interact directly or indirectly, where the grouping is relevant to the characterization of living matter. The NCBI BioSystems Database provides centralized access to biological pathways from several source databases and connects the biosystem records with associated literature, molecular, and chemical data throughout the Entrez system. BioSystem records list and categorize components (illustrated example), such as the genes, proteins, and small molecules involved in a biological system. The companion FLink icon FLink tool, in turn, allows you to input a list of proteins, genes, or small molecules and retrieve a ranked list of biosystems.

This upload contains eight supplementary files in support of X. Dong, G. Patton, A. Nyren, B. Patton and P. Nyren, 2009, "Managing
biological journal citations: The use of a BiBTEX journal titles and abbreviations database in conjunction with LATEX type-setting system," published in Issues in Science & Technology Librarianship, The 2009 Summer Issue (Number 58). DOI:10.5062/F4GH9FVM The article can be accessed at http://www.istl.org/09-summer/article3.html

These documents were originally posted on the following website: https://web.archive.org/web/20130311160032/http://www.infoclearinghouse.com/tiki-index.php?page=LaTeX+Applications

However, the website is longer available as of today (February 27, 2021). To prevent these documents from getting lost, I have decided to post them on zenodo and make them freely available. In this post, some of the file names have been changed. Specifically, Supplementary 1.txt, Supplementary 2.txt,..., Supplementary 5.txt, have been renamed as MyRef.bib, Jshort.bib, Jshort_dot.bib, JLong.bib, and XDRef.bib, respectively.

BioJournalsOK.pdf is a detailed description of the method described by Dong et al. (2009) in ISTL.

MyRef.bib is a short version of XDRef.bib, a collection of 835 eco-physiological references by Dr. Xuejun Dong.

JLong.bib, Jshort.bib, and Jshort_dot.bib are three versions of the same set of 4387 biological journal names database based on an original database by Drs. Lloyd Hough and Geoff Patton at: http://home.ncifcrf.gov/research/bja/

The email address of Dr. Patton is: gwpatton1@yahoo.com

More entries were added by Dr. Xuejun Dong. Either of the three versions of the journal names database can be used in combination with bibliography files in a LaTeX document involving bibliography citations.. In \bibliography{Jnames,bibfile1,bibfile2,...},
always list the journal names data base "Jnames" first, where "Jnames" can be Jshort.bib, Jshort_dot.bib, or JLong.bib.

Supplementary_6.pdf and Supplementary_7.pdf provide additional information about the bibliography databases.

Database that provides access to biological systems and their component genes, proteins, and small molecules, as well as literature describing those biosystems and other related data throughout Entrez. A biosystem, or biological system, is a group of molecules that interact directly or indirectly, where the grouping is relevant to the characterization of living matter. BioSystem records list and categorize components, such as the genes, proteins, and small molecules involved in a biological system. The companion FLink tool, in turn, allows you to input a list of proteins, genes, or small molecules and retrieve a ranked list of biosystems. A number of databases provide diagrams showing the components and products of biological pathways along with corresponding annotations and links to literature. This database was developed as a complementary project to (1) serve as a centralized repository of data; (2) connect the biosystem records with associated literature, molecular, and chemical data throughout the Entrez system; and (3) facilitate computation on biosystems data. The NCBI BioSystems Database currently contains records from several source databases: KEGG, BioCyc (including its Tier 1 EcoCyc and MetaCyc databases, and its Tier 2 databases), Reactome, the National Cancer Institute's Pathway Interaction Database, WikiPathways, and Gene Ontology (GO). It includes several types of records such as pathways, structural complexes, and functional sets, and is desiged to accomodate other record types, such as diseases, as data become available. Through these collaborations, the BioSystems database facilitates access to, and provides the ability to compute on, a wide range of biosystems data. If you are interested in depositing data into the BioSystems database, please contact them.

List of bioinformatic tools for identification of gene and protein homologues.

Maintains and provides archival, retrieval and analytical resources for biological information. Central DDBJ resource consists of public, open-access nucleotide sequence databases including raw sequence reads, assembly information and functional annotation. Database content is exchanged with EBI and NCBI within the framework of the International Nucleotide Sequence Database Collaboration (INSDC). In 2011, DDBJ launched two new resources: DDBJ Omics Archive and BioProject. DOR is archival database of functional genomics data generated by microarray and highly parallel new generation sequencers. Data are exchanged between the ArrayExpress at EBI and DOR in the common MAGE-TAB format. BioProject provides organizational framework to access metadata about research projects and data from projects that are deposited into different databases.

Databases that represent sets of pre-compiled information on biological relationships and associations, interactions and facts which have been extracted from the biomedical literature using Ariadne's MedScan technology. ResNet databases store information harvested from the entire PubMed in a formal structure that allows searching, retrieval and updating by Pathway Studio user. ResNet is seamlessly installed when Pathway Studio is installed. There are several available ResNet databases: *ResNet Mammalian Database includes data for Human, Rat, and Mouse *ResNet Plant Database has data on Arabidopsis, Rice and several other plants. Features of ResNet: *All extracted relations have linked access to the original article or abstract *Synonyms and homologs are included to maintain gene identity and to obviate redundancy in search results *Users can update ResNet as often as required using the MedScan technology built into all Ariadne products *Updates are made available by Ariadne every quarter To purchase Pathway Studio software with ResNet database, for information, or to schedule a web demonstration, call our sales department at (240) 453-6272, or (866) 340-5040 (toll free)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

This record is a comprehensive list of vascular plant species from the Biological Survey of South Australia. Preparation from raw data obtained via the Advanced Ecological Knowledge and Observation System (AEKOS; now deprecated) data portal involved the selection of data fields, the removal of intraspecific taxa (only genus and species used to define individual taxa) and removal of duplicate records and those not determined to species.

Community-wide effort (Challenge) for evaluating text mining and information extraction systems applied to the biological domain. It is focused on the comparison of methods and the community assessment of scientific progress, rather than on the purely competitive aspects. There is a considerable difficulty in constructing suitable gold standard data for training and testing new information extraction systems which handle life science literature. Thus the data sets derived from the BioCreAtIvE challenge - because they have been examined by biological database curators and domain experts - serve as useful resources for the development of new applications as well as helping to improve existing ones. Two main issues are addressed at BioCreAtIvE, both concerned with the extraction of biologically relevant and useful information from the literature. The first one is concerned with the detection of biologically significant entities (names) such as gene and protein names and their association to existing database entries. The second one is concerned with the detection of entity-fact associations (e.g. protein - functional term associations ).

Of interest to pharmaceutical, nutritional, and biomedical researchers, as well as individuals and companies involved with alternative therapies and and herbal products, this database is one of the world's leading repositories of ethnobotanical data, evolving out of the extensive compilations by the former Chief of USDA's Economic Botany Laboratory in the Agricultural Research Service in Beltsville, Maryland, in particular his popular Handbook of phytochemical constituents of GRAS herbs and other economic plants (CRC Press, Boca Raton, FL, 1992). In addition to Duke's own publications, the database documents phytochemical information and quantitative data collected over many years through research results presented at meetings and symposia, and findings from the published scientific literature. The current Phytochemical and Ethnobotanical databases facilitate plant, chemical, bioactivity, and ethnobotany searches. A large number of plants and their chemical profiles are covered, and data are structured to support browsing and searching in several user-focused ways. For example, users can get a list of chemicals and activities for a specific plant of interest, using either its scientific or common name download a list of chemicals and their known activities in PDF or spreadsheet form find plants with chemicals known for a specific biological activity display a list of chemicals with their LD toxicity data find plants with potential cancer-preventing activity display a list of plants for a given ethnobotanical use find out which plants have the highest levels of a specific chemical References to the supporting scientific publications are provided for each specific result. Resources in this dataset:Resource Title: Duke-Source-CSV.zip. File Name: Duke-Source-CSV.zipResource Description: Dr. Duke's Phytochemistry and Ethnobotany - raw database tables for archival purposes. Visit https://phytochem.nal.usda.gov/phytochem/search for the interactive web version of the database.Resource Title: Data Dictionary (preliminary). File Name: DrDukesDatabaseDataDictionary-prelim.csvResource Description: This Data Dictionary describes the columns for each table. [Note that this is in progress and some variables are yet to be defined or are unused in the current implementation. Please send comments/suggestions to nal-adc-curator@ars.usda.gov ]

This spreadsheet contains the information about the specimen API's of GBIF, BOLD Systems, iDigBio, and PlutoF. It lists the endpoints and the documentation URLs in the sheet named "APIs". In the sheet named "Mappings" it lists how to map the non-DwC compliant APIs (BOLD and PlutoF) to DwC-terms.

The data set accompanies the accepted paper in Ecosphere. The data set includes two experimental appraoches to assess the spread and impacts of buffel grass, Cenchrus cilairis, in the Aṉangu Pitjantjatjara Yankunytjatjara (APY) Lands of arid central Australia: a Before-After-Control-Impact (BACI) experiment over 25 years at 15 sites (surveyed in 1994-95 and 2018-19), and a spatially paired-plot (randomised-block) experiment at 18 sites (surveyed in 2018-19). Both experiments spanned two geographic regions (~ 300 km apart) and multiple vegetation communities amongst flat plains and rocky hills landforms. Each experimental design has a plant species data set, and a data set that includes site variables and summed relative cover of plant functional groups. Data collection methodology is described in the accompanying paper, and summarised here.

Each site was one hectare in size. The ecological data was collected in accordance with standard biological survey methods in South Australia (Heard and Channon 1997), including recording of plant species and cover abundance, life form, height class and habitat variables including percent bare earth, litter, rock/strew and soil type (clay percent). Fire history for the previous 25 years was also available from fire scar mapping. Species cover-abundance was estimated in the field using a modified Braun-Blanquet scale and later converted to a raw continuous variable based on the mid-point of the cover class: 1% (1-10 plants, <5% cover); 2% (sparsely present, <5% cover; 3% (plentiful but <5% cover); 15% (5 to 25% cover class); 37% (25 to 50% cover class); 63% (50 to 75% cover class). Buffel grass was recorded on the same scale. Plant species were vouchered and identification checked post-field by the South Australian Hebarium. Plant taxonomy reflects current names (as of 2015) in the Biological Databases of South Australia and taxonomy was aligned between the 1990s and 2020s decades. Recently some species have been split into multiple species (e.g. Acacia aneura, Mulga) but this latest taxonomy was not adopted to retain taxonomic alignment within the dataset. The raw mid-point percent cover was converted to relative percent cover by dividing each species’ (or groups’) raw cover by the summed cover of all species at that site (including buffel grass + understorey + overstorey species). Classification of plants into functional groups was based on field assessed (1) height class + (2) life form, and literature-derived (3) life strategy (perennial or annual) + (4) Native status to South Australia. Height classes were grouped into overstorey (>1m in height) and understorey (≤1m). Summed relative cover for each functional group per site is included in the site and cover data sets to facilitate modelling of cover with site variables. The plant species data sets is the full list of species and cover abundance recorded at each site which can be used for analysis of community composition, diversity, turnover or individual species change. Sensitive species (one species in this dataset) has had the coordinates denatured by 10km due according to the requirements of the Biological Database of South Australia for sensitive species. All coordinates provided in MGA 52 Eastings and Northings (UTM, Australian National Grid).

The authors wish to acknowledge Traditional Owners and Aṉangu Pitjantjatjara Yankunytjatjara (APY) Lands Organisation who gave permission for collaboration, data collection, photographs and reporting on and about their Traditional Lands. Data is jointly the Intellectual Property of Aṉangu as the Traditional Owners and the author team, and approval has been granted for research and publication use with appropriate acknowledgment of Aṉangu and the author team. The 1990s baseline data is also the Intellectual Property of the South Australian Government and is made publicly available under a licencing agreement with the Biological Databases of South Australia (licence number 2412). Many people assisted in the field during the 1990s and 2020s vegetation surveys and are wholly acknowledged. APY Land Management, Alinytjara Wilurara Landscape Board, Central Land Council, Ten Deserts Project, Charles Darwin University, South Australian Department for Environment and Water, State Herbarium of South Australia, Holsworth Wildlife Research Endowment, Jill Landsberg Trust and Ecological Society of Australia all provided either funding and/or in-kind support of the project. Study conducted with APY Executive Board approval, South Australian Scientific Permit Q26782 and Northern Territory Wildlife Permit 63104.

An integrated knowledgebase focused on protein termini, their formation by proteases and functional implications. It contains information about the processing and the processing state of proteins and functional implications thereof derived from research literature, contributions by the scientific community and biological databases. It lists more than 120,000 N- and C-termini and almost 10,000 cleavages. TopFIND is a resource for comprehensive coverage of protein N- and C-termini discovered by all available in silico, in vitro as well as in vivo methodologies. It makes use of existing knowledge by seamless integration of data from UniProt and MEROPS and provides access to new data from community submission and manual literature curating. It renders modifications of protein termini, such as acetylation and citrulination, easily accessible and searchable and provides the means to identify and analyse extend and distribution of terminal modifications across a protein. The data is presented to the user with a strong emphasis on the relation to curated background information and underlying evidence that led to the observation of a terminus, its modification or proteolytic cleavage. In brief the protein information, its domain structure, protein termini, terminus modifications and proteolytic processing of and by other proteins is listed. All information is accompanied by metadata like its original source, method of identification, confidence measurement or related publication. A positional cross correlation evaluation matches termini and cleavage sites with protein features (such as amino acid variants) and domains to highlight potential effects and dependencies in a unique way. Also, a network view of all proteins showing their functional dependency as protease, substrate or protease inhibitor tied in with protein interactions is provided for the easy evaluation of network wide effects. A powerful yet user friendly filtering mechanism allows the presented data to be filtered based on parameters like methodology used, in vivo relevance, confidence or data source (e.g. limited to a single laboratory or publication). This provides means to assess physiological relevant data and to deduce functional information and hypotheses relevant to the bench scientist. TopFIND PROVIDES: * Integration of protein termini with proteolytic processing and protein features * Displays proteases and substrates within their protease web including detailed evidence information * Fully supports the Human Proteome Project through search by chromosome location CONTRIBUTE * Submit your N- or C-termini datasets * Contribute information on protein cleavages * Provide detailed experimental description, sample information and raw data