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http://www-pmr.ch.cam.ac.uk/wiki/Oscar3
OSCAR is software for the semantic annotation of chemistry papers. The modules OPSIN (a name to structure converter) and ChemTok (a tokeniser for chemical text) are also available as standalone libraries. This tool for shallow, chemistry-specific parsing of chemical documents identifies (or attempts to identify): * Chemical names: singular nouns, plurals, verbs etc., also formulae and acronyms, some enzymes and reaction names. * Ontology terms: if you can do it by string-matching, you can get OSCAR to do it. * Chemical data: Spectra, melting/boiling point, yield etc. in experimental sections. In addition, where possible the chemical names that are detected are annotated with structures, either via lookup or name-to-structure parsing (OPSIN), and with identifiers from the chemical ontology ChEBI Current work on OSCAR3 by Peter Corbett focuses on its use in SciBorg, a framework for the deep parsing of chemical text. OSCAR3 also includes the Oscar Server, a Jetty-powered set of servlets. These provide the following services: * Parsing of text/HTML by OSCAR. * Text/InChI/SMILES/SMILES substructues/SMILES similarity search of papers, coupled with keyword and ontology-based search, using Lucene and the CDK. * List of all names found / all names that co-occur with a search term or terms. * Online management of a chemical/stopword lexicon. * Manual editing of SciXML fragments containing named entities, for creating of gold standards and training data. Oscar3 can be found on SourceForge: http://sourceforge.net/projects/oscar3-chem/
Proper citation: Oscar3 (RRID:SCR_004561) Copy
http://www.brainarchitecture.org/mouse-home
An atlas project whose goal is to enerate brainwide maps of inter-regional neural connectivity that specify the inputs and outputs of every brain region, at a "mesoscopic" level of analysis. A 3D injection viewer is used to view the mouse brain. To determine the outputs of a brain region, anterograde tracers are used which are taken up by neurons locally ("the input"), then transported actively down the axons to the "output regions." The whole brain is then sliced thinly, and each slice is digitally imaged. These 2-D images are reconstructed in 3D. The majority of the resulting 3-D brain image is unlabeled. Only the injected region and its output regions have tracer in them, allowing for identification of this small fraction of the connectivity map. This procedure is repeated identically, to account for individual variability. To determine the inputs to the same brain region as above, a retrograde tracer is injected in the same stereotaxic location ("the input"), and the process is repeated. In order to accumulate data from different mice (each of whom has a slightly different brain shape and size), 3-D spatial normalization is performed using registration algorithms. These gigapixel images of whole-brain sections can be zoomed to show individual neurons and their processes, providing a "virtual microscope." Each sampled brain is represented in about 500 images, each image showing an optical section through a 20 micron-thick slice of brain tissue. A multi-resolution viewer permits users to journey through each brain, following the pathways taken through three-dimensional brain space by tracer-labeled neuronal pathways. A key point is that at the mid-range "mesoscopic" scale, the team expects to assemble a picture of connections that are stereotypical and probably genetically determined in a species-specific manner. By dividing the volume of a hemisphere of the mouse brain into 250 equidistant, predefined grid-points, and administering four different kinds of tracer injections at each grid point -- in different animals of the same sex and age a complete wiring diagram that will be stitched together in "shotgun" fashion from the full dataset.
Proper citation: Mouse Brain Architecture Project (RRID:SCR_004683) Copy
http://metagenomics.atc.tcs.com/binning/SOrt-ITEMS/
Sequence orthology based software for improved taxonomic estimation of metagenomic sequences., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: SOrt-ITEMS (RRID:SCR_004716) Copy
http://en.wikibooks.org/wiki/Orthopaedic_Surgery
Orthopaedic Surgery is a collaborative wikibook of orthopedic surgery. *Preface *Chapter 1: Basic Sciences *Chapter 2: Upper Limb *Chapter 3: Foot and Ankle *Chapter 4: Spine *Chapter 5: Hand and Microsurgery *Chapter 6: Pediatric Orthopedics *Chapter 7: Adult Reconstruction *Chapter 8: Sports Medicine *Chapter 9: Musculoskeletal Tumors *Chapter 10: Injury *Chapter 11: Surgical Procedures *Chapter 12: Rehabilitation *Chapter 13: Practice
Proper citation: Orthopaedic Surgery (RRID:SCR_004715) Copy
Located in the city of Galway in Ireland.
Proper citation: National University of Ireland; Galway; Ireland (RRID:SCR_004677) Copy
A multiple-sample, technology-aware SNP and indel caller.
Proper citation: UnifiedGenotyper (RRID:SCR_004710) Copy
http://www.ncbi.nlm.nih.gov/Structure/cblast/cblast.cgi?
The NCBI Related Structures tool allows you to find 3D structures from the Molecular Modeling Database (MMDB) that are similar in sequence to a query protein. Although the query protein may not yet have a resolved structure, the 3D shape of a similar protein sequence can shed light on the putative shape and biological function of the query protein. CBLAST is a tool that compares a query protein sequence against all protein sequences from resolved 3D structures by using protein BLAST against the PDB data set. The purpose is to find representative 3D structures for the query and/or its homologs, as available. Each record in the Entrez Protein database has been CBLAST''ed and the search results are available as Related Structures in the Links menu of Entrez Protein records. You can also enter a protein query sequence directly into the CBLAST search page in order to find its sequence-similar 3D structure records. The search results can be viewed in Cn3D (hence the name CBLAST), which displays an alignment of the query protein to the related structure''s sequence and allows you to interactively examine the sequence-structure relationship.
Proper citation: CBLAST (RRID:SCR_004711) Copy
The Systems Biology Graphical Notation (SBGN) project aims to develop high quality, standard graphical languages for representing biological processes and interactions. Each SBGN language is based on the consensus of the broad international SBGN community of biologists, curators and software developers. Over the course of its development many individuals, organizations and companies made invaluable contributions to the SBGN through participating in discussions and meetings, providing feedback on the documentation and worked examples, adopting the standard and spreading the word. Circuit diagrams and Unified Modeling Language diagrams are just two examples of standard visual languages that help accelerate work by promoting regularity, removing ambiguity and enabling software tool support for communication of complex information. Ironically, despite having one of the highest ratios of graphical to textual information, biology still lacks standard graphical notations. The recent deluge of biological knowledge makes addressing this deficit a pressing concern. Toward this goal, we present the Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists. SBGN consists of three complementary languages: process diagram, entity relationship diagram and activity flow diagram. Together they enable scientists to represent networks of biochemical interactions in a standard, unambiguous way. We believe that SBGN will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge, from gene regulation, to metabolism, to cellular signaling. A list of software packages known to provide (or have started to develop) support for SBGN notations is available.
Proper citation: Systems Biology Graphical Notation (RRID:SCR_004671) Copy
http://www.openanesthesia.org/
OpenAnesthesia.org is a wiki promoting evidence-based medicine in anesthesiology, critical care and pain management. It is divided into several, major Units (Anesthesia Text, Critical Care Manual, Practice-Changing Articles, Controversies in Anesthesia, ABA keywords, Audio/Video Archives, CME, GME, Pharmacology...), each of which is subdivided into Chapters (or in some cases, even smaller subdivisions, such as sections, individual key words, topics, points of interest, or bibliographic references). The goal of Anasthesia Text is to collect and distribute evidence-based information regarding all aspects of anesthesia. This section is similar to a traditional textbook in the broad range of topics covered, but different in that it will provide this information in the form of a wiki (i.e. anyone can edit, add, or subtract to it). OpenAneshesia.org provides anesthesia residents with GME credit and Program Directors with a tool to document core competency activities for Accreditation Council for Graduate Medical Education (ACGME)-mandated learning portfolios. Residents are invited invited to read the Anesthesia & Analgesia article of the month and listen to an interview with one of the article''s authors. During the interview, the author will discuss the specifics of the article as well as general topics geared towards improving each resident''s appreciation of basic or clinical research. After listening to the podcast and reading the article, residents can answer 5 questions in order to demonstrate their mastery of the topics discussed (similar to the Anesthesia & Analgesia Continuing Medical Education (CME) section). Like the CME section, after demonstrating proficiency, a resident will receive a printable certificate that will specify which ACGME core competencies were addressed in the article and interview. The certificates can be put in each resident''s ACGME-required learning portfolio.
Proper citation: OpenAnesthesia.org (RRID:SCR_004547) Copy
http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0075146
An R Package to Study Gene Spatial Neighbourhoods with Multi-Omics Annotations.
Proper citation: NuChart (RRID:SCR_004703) Copy
http://www.chdifoundation.org/
A private, not-for-profit research organization that serves as an international collaborative enabler in order to discover drugs that slow the progression of Huntington's disease (HD). The activities of CHDI extend from exploratory biology to the identification and validation of therapeutic targets, and from drug discovery and development to clinical studies and trials. CHDI works with biotech and pharmaceutical companies and funds and works with academic HD researchers at universities.
Proper citation: CHDI Foundation (RRID:SCR_004622) Copy
https://bams1.org/ontology/viewer.php
Ontology designed for neuroscience. Includes complete set of concepts that describe parts of rat nervous system, growing set of concepts that describe neuron populations identified in different brain regions, and relationships between concepts.
Proper citation: BAMS Neuroanatomical Ontology (RRID:SCR_004616) Copy
http://matsen.fhcrc.org/pplacer/
Software that places query sequences on a fixed reference phylogenetic tree to maximize phylogenetic likelihood or posterior probability according to a reference alignment. Pplacer is designed to be fast, to give useful information about uncertainty, and to offer advanced visualization and downstream analysis.
Proper citation: Pplacer (RRID:SCR_004737) Copy
Standalone software programs that can be used to calculate how well tetranucleotide usage patterns in DNA sequences correlate. Such correlations can provide valuable hints on the relatedness of DNA sequences.
Proper citation: TETRA (RRID:SCR_004573) Copy
http://www.ncbi.nlm.nih.gov/biosystems/
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.
Proper citation: NCBI BioSystems Database (RRID:SCR_004690) Copy
http://www.ganfyd.org/index.php?title=Main_Page
Simply put ganfyd is an evolving textbook of medicine: a free medical knowledge base that anyone can read and any registered medical practitioner may edit. This collaborative medical reference by medical professionals and invited non-medical experts is based around the wiki format, enabling true sharing of knowledge. Please join and help us to create a great source of information and experience! Ganfyd is the first of its type and relies on your contributions to make it a truly world-class resource. Contents: * Medical Specialties * Surgical Specialties * Primary Care * Public Health * Laboratory-based specialties * Imaging Specialties * Basic Medical Sciences * Miscellaneous * Women''s health * Survival Guides * How-tos & Practical Advice * Resources for Trainees * Computing * Medical Dictionary
Proper citation: Ganfyd - Get A Note From Your Doctor (RRID:SCR_004606) Copy
Non-profit academic organization for research and services in bioinformatics. Provides freely available data from life science experiments, performs basic research in computational biology, and offers user training programme, manages databases of biological data including nucleic acid, protein sequences, and macromolecular structures. Part of EMBL.
Proper citation: European Bioinformatics Institute (RRID:SCR_004727) Copy
A web-based browser for Gene Ontology terms and annotations, which is provided by the UniProtKB-GOA group at the EBI. It is able to offer a range of facilities including bulk downloads of GO annotation data which can be extensively filtered by a range of different parameters and GO slim set generation. The software for QuickGO is freely available under the Apache 2 license. QuickGO can supply GO term information and GO annotation data via REST web services.
Proper citation: QuickGO (RRID:SCR_004608) Copy
UKM affirms integration of faith in Allah and constructive knowledge along with amalgamation of theory and practice as core fundamentals in advancement of knowledge, building of educated society and development of university.
Proper citation: National University of Malaysia; Selangor; Malaysia (RRID:SCR_004724) Copy
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