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http://www.blipkit.org/

Biomedical Logical Programming (Blip) is a research-oriented deductive database and prolog application library for handling biological and biomedical data. It includes packages for advanced querying of ontologies and annotations. Blip underpins the Obol tool. Here are some distinguishing characteristics of Blip * Lightweight. Bloat-free: Blip only has as many modules as it needs to do its job. * Fast. * Declarative. Say what you want to do, not how you want to do it * Blip can be Query-oriented: specify your data sources and ask your query * Blip can be Application-oriented: it is designed to be used as an application library used by other bioinformatics tools * Mature and fully functional ontology module for handling both OBO-style ontologies and OWL ontologies. * Modules for handling biological sequences and sequence features. (currently limited functionality, added as needed) * A systems biology module for querying pathway and interaction data. (currently limited functionality, added as needed) * Relational database integration. SQL can be viewed as a highly restricted dialect of Prolog. Although the SWI-Prolog in-memory database is fast and scalable, sometimes it is nice to be able to fetch data from an external database. Blip contains a generic SQL utility module and predicate mappings for the GO database, Ensembl and Chado * Integration with a variety of bioinformatics file formats. SWI-Prolog has a variety of fast libraries for dealing with XML, RDF and tabular data files. Blip provides bridges from bio file formats encoded using these syntaxes into its native models. For other syntaxes, Blip seamlessly integrates other packages such as BioPerl and go-perl. Although these dependencies require extra installation, there is no point reinventing the wheel * Rapid development of web applications. Blip extends SWI-Prolog''''s excellent http support with a simple and powerful logical-functional-programming style application server, serval. This has been used to prototype a fully-featured next-generation replacement for the GO project amigo browser. * Scalable. Blip is not intended to be a toy system on toy data (although it is happy to be used as a toy if you like!). It is intended to be used as an application component and a tool operating on real-world biological and biomedical data Blip is written in SWI-Prolog, a fast, robust and scalable implementation of ISO Prolog. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Blip: Biomedical Logic Programming (RRID:SCR_005733) Copy   

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http://brainnetworks.sourceforge.net

Brain Networks: Code to perform network analysis on brain imaging data.

Proper citation: Brain Networks (RRID:SCR_005841) Copy   

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http://www.clo-ontology.org/

A community-driven ontology that is developed to standardize and integrate cell line information and support computer-assisted reasoning. Its focus is on permanent cell lines from culture collections. Upper ontology structures that frame the skeleton of CLO include Basic Formal Ontology and Relation Ontology. Cell lines contained in CLO are associated with terms from other ontologies such as Cell Type Ontology, NCBI Taxonomy, and Ontology for Biomedical Investigation. A common design pattern for the cell line is used to model cell lines and their attributes, the Jurkat cell line provides ane xample. Currently CLO contains over 36,000 cell line entries obtained from ATCC, HyperCLDB, Coriell, and bymanual curation. The cell lines are derived from 194 cell types, 656 anatomical entries, and 217 organisms. The OWL-based CLO is machine-readable and can be used in various applications. The CLO development has become a community effort with international collaborations. The development consortium includes experts from all over the world: the USA, Europe, and Japan.

Proper citation: Cell Line Ontology (RRID:SCR_005840) Copy   

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http://www.cancer.org/

The American Cancer Society is the nationwide, community-based, voluntary health organization dedicated to eliminating cancer as a major health problem by preventing cancer, saving lives, and diminishing suffering from cancer, through research, education, advocacy, and service. Together with our millions of supporters, the American Cancer Society (ACS) saves lives and creates a world with less cancer and more birthdays by helping people stay well, helping people get well, by finding cures, and by fighting back. Headquartered in Atlanta, Georgia, the ACS has 12 chartered Divisions, more than 900 local offices nationwide, and a presence in more than 5,100 communities.

Proper citation: American Cancer Society (RRID:SCR_005756) Copy   

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http://crdd.osdd.net/raghava/ccpdb/

ccPDB (Compilation and Creation of datasets from PDB) is designed to provide service to scientific community working in the field of function or structure annoation of proteins. This database of datasets is based on Protein Data Bank (PDB), where all datasets were derived from PDB. ccPDB have four modules; i) compilation of datasets, ii) creation of datasets, iii) web services and iv) Important links. * Compilation of Datasets: Datasets at ccPDB can be classified in two categories, i) datasets collected from literature and ii) datasets compiled from PDB. We are in process of collecting PDB datasetsfrom literature and maintaining at ccPDB. We are also requesting community to suggest datasets. In addition, we generate datasets from PDB, these datasets were generated using commonly used standard protocols like non-redundant chains, structures solved at high resolution. * Creation of datasets: This module developed for creating customized datasets where user can create a dataset using his/her conditions from PDB. This module will be useful for those users who wish to create a new dataset as per ones requirement. This module have six steps, which are described in help page. * Web Services: We integrated following web services in ccPDB; i) Analyze of PDB ID service allows user to submit their PDB on around 40 servers from single point, ii) BLAST search allows user to perform BLAST search of their protein against PDB, iii) Structural information service is designed for annotating a protein structure from PDB ID, iv) Search in PDB facilitate user in searching structures in PDB, v)Generate patterns service facility to generate different types of patterns required for machine learning techniques and vi) Download useful information allows user to download various types of information for a given set of proteins (PDB IDs). * Important Links: One of major objectives of this web site is to provide links to web servers related to functional annotation of proteins. In first phase we have collected and compiled these links in different categories. In future attempt will be made to collect as many links as possible.

Proper citation: ccPDB - Compilation and Creation of datasets from PDB (RRID:SCR_005870) Copy   

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https://www.antigenix.com/

An Antibody supplier

Proper citation: Antigenix America (RRID:SCR_005871) Copy   

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http://utrdb.ba.itb.cnr.it/

UTRdb/UTRsite is a portal to other databases, including Nucleotide Sequence Databases, Protein Sequence Databases, other Sequence databanks, Untranslated Nucleotide Sequence Databases, Mitochondrial Databases, Mutation Databases, and others. The site also allows users to start long-term permanent projects or just to do quick searches, depending on the user''s needs.

Proper citation: UTRdb/UTRsite (RRID:SCR_005868) Copy   

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http://www.ici.upmc.fr/cluego/

A Cytoscape plug-in that visualizes the non-redundant biological terms for large clusters of genes in a functionally grouped network. It can be used in combination with GOlorize. The identifiers can be uploaded from a text file or interactively from a network of Cytoscape. The type of identifiers supported can be easily extended by the user. ClueGO performs single cluster analysis and comparison of clusters. From the ontology sources used, the terms are selected by different filter criteria. The related terms which share similar associated genes can be combined to reduce redundancy. The ClueGO network is created with kappa statistics and reflects the relationships between the terms based on the similarity of their associated genes. On the network, the node colour can be switched between functional groups and clusters distribution. ClueGO charts are underlying the specificity and the common aspects of the biological role. The significance of the terms and groups is automatically calculated. ClueGO is easy updatable with the newest files from Gene Ontology and KEGG. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ClueGO (RRID:SCR_005748) Copy   

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http://louisville.edu/

Public research university in Louisville, Kentucky. It is part of the Kentucky state university system.

Proper citation: University of Louisville; Kentucky; USA (RRID:SCR_005749) Copy   

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http://estscan.sourceforge.net/

ESTScan is a program that can detect coding regions in DNA sequences, even if they are of low quality. ESTScan will also detect and correct sequencing errors that lead to frameshifts. ESTScan is not a gene prediction program , nor is it an open reading frame detector. In fact, its strength lies in the fact that it does not require an open reading frame to detect a coding region. As a result, the program may miss a few translated amino acids at either the N or the C terminus, but will detect coding regions with high selectivity and sensitivity. ESTScan takes advantages of the bias in hexanucleotide usage found in coding regions relative to non-coding regions. This bias is formalized as an inhomogeneous 3-periodic fifth-order Hidden Markov Model (HMM). Additionally, the HMM of ESTScan has been extended to allows insertions and deletions when these improve the coding region statistics.

Proper citation: ESTScan (RRID:SCR_005742) Copy   

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http://www.mellon.org/

The Andrew W. Mellon Foundation currently makes grants in five core program areas: * Higher Education and Scholarship * Scholarly Communications and Information Technology * Art History, Conservation, and Museums * Performing Arts * Conservation and the Environment Within each of its core programs, the Foundation concentrates most of its grantmaking in a few areas. Institutions and programs receiving support are often leaders in fields of Foundation activity, but they may also be promising newcomers, or in a position to demonstrate new ways of overcoming obstacles to achieve program goals. Our grantmaking philosophy is to build, strengthen and sustain institutions and their core capacities, rather than be a source for narrowly defined projects. As such, we develop thoughtful, long-term collaborations with grant recipients and invest sufficient funds for an extended period to accomplish the purpose at hand and achieve meaningful results.

Proper citation: Andrew W. Mellon Foundation (RRID:SCR_005864) Copy   

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http://simile.mit.edu/

SIMILE, a joint project conducted by the MIT Libraries and MIT CSAIL, was focused on developing robust, open source tools that empower users to access, manage, visualize and reuse digital assets. SIMILE seeks to enhance interoperability among digital assets, schemata/vocabularies/ontologies, metadata, and services. A key challenge is that the collections which must inter-operate are often distributed across individual, community, and institutional stores. We seek to be able to provide end-user services by drawing upon the assets, schemata/vocabularies/ontologies, and metadata held in such stores. SIMILE will leverage and extend DSpace, enhancing its support for arbitrary schemata and metadata, primarily though the application of RDF and semantic web techniques. The project also aims to implement a digital asset dissemination architecture based upon web standards. The dissemination architecture will provide a mechanism to add useful views to a particular digital artifact (i.e. asset, schema, or metadata instance), and bind those views to consuming services. To guide the SIMILE effort we will focus on well-defined, real-world use cases in the libraries domain. Since parallel work is underway to deploy DSpace at a number of leading research libraries, we hope that such an approach will lead to a powerful deployment channel through which the utility and readiness of semantic web tools and techniques can be compellingly demonstrated in a visible and global community. The SIMILE Project and its members are fully committed to the open source principles of software distribution and open development and for this reason, it releases the created intellectual property (both software and reports) under a BSD-style license. The SIMILE Project Team Members gladly welcome community efforts.

Proper citation: SIMILE (RRID:SCR_005862) Copy   

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http://www.stanford.edu/~nigam/cgi-bin/dokuwiki/doku.php?id=clench

Cluster Enrichment (CLENCH) allows A. thaliana researchers to perform automated retrieval of GO annotations from TAIR and calculate enrichment of GO terms in gene group with respect to a reference set. Before calculating enrichment, CLENCH allows mapping of the returned annotations to arbitrary coarse levels using GO slim term lists (which can be edited by the user) and a local installation of GO. Platform: Windows compatible, Linux compatible,

Proper citation: CLENCH (RRID:SCR_005735) Copy   

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http://www.auanet.org/content/homepage/homepage.cfm

The American Urological Association (AUA), founded in 1902, is the premier professional association for the advancement of urologic patient care, and works to ensure that its more than 18,000 members are current on the latest research and practices in urology. The AUA also pursues its mission of fostering the highest standards of urologic care by providing a wide range of servicesincluding publications, research, the Annual Meeting, continuing medical education (CME) and the formulation of health policy.

Proper citation: American Urological Association (RRID:SCR_005859) Copy   

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http://drcat.sourceforge.net/

Data resource catalog that collates metadata on bioinformatics Web-based data resources including databases, ontologies, taxonomies and catalogues. An entry includes information such as resource identifier(s), name, description and URL. ''''Query'''' lines are defined for each resource that describe what type(s) of data are available, in what format, how (by what identifier) the data can be retrieved and from where (URL). DRCAT was developed to provide more extensive data integration for EMBOSS, but it has many applications beyond EMBOSS. DRCAT entries (including ''''Query'''' lines) are annotated with terms from the EDAM ontology of common bioinformatics concepts.

Proper citation: DRCAT Resource Catalogue (RRID:SCR_005931) Copy   

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https://fairsharing.org/standards/

Catalogue to: 1, centralize community-developed bioscience standards, linking to policies, other portals, open access resources and lists of tools and databases implementing the standards; 2. develop and maintain a set of criteria for assessing the usability and popularity of the standards, also the interoperability and relations among them; 3. foster interoperability, addressing overlaps and duplication of efforts that hamper their wider uptake and interfere with the creation of standards-compliant systems. Research community, funding agencies, and journals participate in the development of reporting standards for the bioscience domain to ensure that shared experiments are reported with enough information to be comprehensible and (in principle) reproducible, compared or integrated. Similar trends in both the regulatory arena and commercial science. The BioSharing catalogue classifies standards into three types: * reporting requirements (minimal information checklists to report of the same core set of information) * terminological artifacts (such as controlled vocabularies and ontologies to describe the information) * exchange formats (to communicate the information) You can sort columns and browse the reporting guidelines content, or you can view all the standards, or reporting guidelines, or terminological artifacts or exchange formats only. Contribute and help build the catalogue.

Proper citation: FAIRSharing Catalogue of Standards (RRID:SCR_005926) Copy   

•   Source: SciCrunch Registry

http://dictybase.org/Dicty_Info/dicty_anatomy_ontology.html

An ontology to describe Dictyostelium where the structural makeup of Dictyostelium and its composing parts including the different cell types, throughout its life cycle is defined. There are two main goals for this new tool: (1) promote the consistent annotation of Dictyostelium-specific events, such as phenotypes (already in use), and in the future, of gene expression information; and (2) encourage researchers to use the same terms with the same intended meaning. To this end, all terms are defined. The complete ontology can be browsed using EBI''s ontology browser tool. (http://www.ebi.ac.uk/ontology-lookup/browse.do?ontName=DDANAT)

Proper citation: Dictyostelium Anatomy Ontology (RRID:SCR_005929) Copy   

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https://array.nci.nih.gov/caarray/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on Sep 18, 2018. Open-source, web and programmatically accessible microarray data management system. caArray guides the annotation and exchange of array data using a federated model of local installations whose results are shareable across the cancer Biomedical Informatics Grid (caBIG). caArray furthers translational cancer research through acquisition, dissemination and aggregation of semantically interoperable array data to support subsequent analysis by tools and services on and off the Grid. As array technology advances and matures, caArray will extend its logical library of assay management.

Proper citation: caArray (RRID:SCR_006053) Copy   

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http://purl.bioontology.org/ontology/RCD

Ontology of clinical terms Version 3 (CTV3) (Read Codes) (Q199): National Health Service National Coding and Classification Centre

Proper citation: Read Codes Clinical Terms Version 3 (RRID:SCR_006055) Copy   

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http://genomefoundation.org/index.php/Main_Page

The Genome Foundation (AKA Genome Research Foundation) is a fully government accredited and registered non-profit research foundation. GRF aims to provide genome philosophy, science, and technology. GRF is a nonprofit publisher, and research and advocacy organization to promote completely free publication of knowledge with minimum restriction. Our core objectives are to: * Provide ways to overcome unnecessary barriers to immediate availability, access, and use of research * Pursue a publishing strategy that optimizes the openness, quality, and integrity of the publication process * Develop innovative approaches to the assessment, organization, and reuse of ideas and data Genome Foundation Research * Personalized Medicine * Personal Genomics * AngioGenesis drug * Bioinformatics * RNA expression * Protein structure * Human Genome Rights Projects at Genome Foundation * The Human Genome Rights * Human Genome Rights Petition * Free Personal Genome Sequencing Project * Free Personal Genome Sequencing Petition * Tiger Genome Initiative: Amur Tiger and big cat genomes * Whale Genome Project

Proper citation: Genome Research Foundation (RRID:SCR_006056) Copy   

•   Source: SciCrunch Registry