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http://thedata.org/citation/standard
Citation standard that offers proper recognition to authors as well as permanent identification through the use of global, persistent identifiers in place of URLs, which can change frequently. Use of universal numerical fingerprints (UNFs) guarantees to the scholarly community that future researchers will be able to verify that data retrieved is identical to that used in a publication decades earlier, even if it has changed storage media, operating systems, hardware, and statistical program format.
Proper citation: Universal Numerical Fingerprint (RRID:SCR_005912) Copy
https://adaptivedisclosure.wordpress.com/aida/
A generic set of components that can perform a variety of tasks, such as learn new pattern recognition models, perform specialized search on resource collections, and store knowledge in a repository. W3C standards are used to make data accessible and manageable with semantic web technologies such as OWL, RDF(S), and SKOS. The AIDA Toolkit is directed at groups of knowledge workers that cooperatively search, annotate, interpret, and enrich large collections of heterogeneous documents from diverse locations. The server offers services for: text indexing and statistics, metadata storage and querying, thesaurus reasoning, annotation, text retrieval, spelling correction, synonym detection, and model learning.
Proper citation: AIDA Toolkit (RRID:SCR_005914) Copy
The Roth Laboratory is designing and interpreting large-scale experiments to understand pathway structure and its relationship to phenotype and human disease. Software for research focused on a specific research goal is available. Current experimental interests: * Exploiting parallel sequencing technology to phenotype all pairwise gene deletion combinations in S. cerevisiae, with initial application to genes involved in transcription. * Generation of S. cerevisiae strains carrying dozens of chosen targeted deletions, with initial application to delete all ABC transporters imparting multidrug resistance. * Targeted insertion of gene sets encoding entire human pathways into S. cerevisiae, with initial application to genes involved in drug metabolism. Current computational interests: * Systematic analysis of genetic interaction to reveal redundant systems and order of action in genetic pathways * Integrating large-scale studies - including phenotype, genetic epistasis, protein-protein and transcription-regulatory interactions and sequence patterns - to quantitatively assign function to genes and guide experimentation and disease association studies. * Alternative splicing and its relationship to protein interaction networks.
Proper citation: Roth Laboratory (RRID:SCR_005711) Copy
http://www.umich.edu/~neurosci/
The Graduate Program at the University of Michigan was constituted in 1971, making it the longest-standing neuroscience graduate program in the United States. We are a collegial and interactive group of 75 students and 115 faculty that perform research across the breadth of the neuroscience field. Neuroscience graduate students on this campus form a cohesive group, which promotes interactions among the faculty, making the Graduate Program the nexus of the neuroscience community. Graduates receive a Ph.D. in Neuroscience, which provides tremendous flexibility in choosing one's career path. There are more than 100 alumni of our Program, and these graduates work in academic research, industrial research and development, academic medicine and biotechnology. Our program captures the excitement and interaction intrinsic to the field of neuroscience. Students can seek admission to the Neuroscience Program by three different routes direct application to the Neuroscience Program, application via the Program in Biomedical Sciences and application via the Medical Scientist Training Program.
Proper citation: University of Michigan Department of Neuroscience Graduate Program (RRID:SCR_006002) Copy
http://bioinformatics.charite.de/voronoia/
Voronoia is a program suite to analyse and visualize the atomic packing of protein structures. It is based on the Voronoi Cell method and can be used to estimate the quality of a protein structure, e.g. by comparing the packing density of buried atoms to a reference data set or by highlighting protein regions with large packing defects. Voronoia is also targeted to detect locations of putative internal water or binding sites for ligands. Accordingly, Voronoia is beneficial for a broad range of protein structure approaches. It is applicable as a standalone version coming with a user friendly GUI or, alternatively, as a Pymol Plugin. Finally, Voronoia is also available as an easy to use webtool to process user defined PDB-files or to asses precalculated packing files from DOPP, the regularly updated Dictionary of Packing in Proteins.
Proper citation: Voronoia (RRID:SCR_006005) Copy
http://www.digital-scholarship.org/sepb/sepb.html
Bibliography with over 3,800 selected English-language articles, books, and other printed and electronic sources that are useful in understanding scholarly electronic publishing efforts on the Internet. It covers a wide range of topics, such as digital copyright, digital libraries, digital preservation, digital repositories, e-books, e-journals, license agreements, metadata, and open access. It includes Scholarly Electronic Publishing Resources, a selective directory of related Web sites, and the Scholarly Electronic Publishing Weblog, a frequently updated list of new publications and other resources that may be of interest to bibliography readers. Most sources have been published from January 1, 1990 through October 30, 2011; however, a limited number of earlier key sources are also included. The bibliography includes links to freely available versions of included works. It does not include digital media works (such as MP3 files), editorials, e mail messages, letters to the editor, daily newspaper articles, presentation slides or transcripts, or weblog postings. An archive of prior versions of SEPB is available as a downloadable compressed file (.zip) that includes all versions of the bibliography. The Scholarly Electronic Publishing Bibliography 2010 is available as a paperback (466 pages, $18.95, ISBN-10: 1456453289 and ISBN-13: 9781456453282) and an open access PDF file.
Proper citation: Scholarly Electronic Publishing Bibliography (RRID:SCR_005949) Copy
http://www.ebi.ac.uk/Tools/pfa/iprscan/
Software package for functional analysis of sequences by classifying them into families and predicting presence of domains and sites. Scans sequences against InterPro's signatures. Characterizes nucleotide or protein function by matching it with models from several different databases. Used in large scale analysis of whole proteomes, genomes and metagenomes. Available as Web based version and standalone Perl version and SOAP Web Service.
Proper citation: InterProScan (RRID:SCR_005829) Copy
Data analysis service to predict the function of your favorite genes and gene sets. Indexing 1,421 association networks containing 266,984,699 interactions mapped to 155,238 genes from 7 organisms. GeneMANIA interaction networks are available for download in plain text format. GeneMANIA finds other genes that are related to a set of input genes, using a very large set of functional association data. Association data include protein and genetic interactions, pathways, co-expression, co-localization and protein domain similarity. You can use GeneMANIA to find new members of a pathway or complex, find additional genes you may have missed in your screen or find new genes with a specific function, such as protein kinases. Your question is defined by the set of genes you input. If members of your gene list make up a protein complex, GeneMANIA will return more potential members of the protein complex. If you enter a gene list, GeneMANIA will return connections between your genes, within the selected datasets. GeneMANIA suggests annotations for genes based on Gene Ontology term enrichment of highly interacting genes with the gene of interest. GeneMANIA is also a gene recommendation system. GeneMANIA is also accessible via a Cytoscape plugin, designed for power users. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: GeneMANIA (RRID:SCR_005709) Copy
http://bishopw.loni.ucla.edu/AIR5/
A tool for automated registration of 3D (and 2D) images within and across subjects and within and sometimes across imaging modalities. The AIR library can easily incorporate automated image registration into site specific programs adapted to your particular needs.
Proper citation: Automated Image Registration (RRID:SCR_005944) Copy
http://www.ebi.ac.uk/webservices/whatizit/info.jsf
A text processing system that allows you to do textmining tasks on text. It is great at identifying molecular biology terms and linking them to publicly available databases. Whatizit is also a Medline abstracts retrieval/search engine. Instead of providing the text by Copy&Paste, you can launch a Medline search. The abstracts that match your search criteria are retrieved and processed by a pipeline of your choice. Whatizit is also available as 1) a webservice and as 2) a streamed servlet. The webservice allows you to enrich content within your website in a similar way as in the wikipedia. The streamed servlet allows you to process large amounts of text.
Proper citation: Whatizit (RRID:SCR_005824) Copy
http://estbioinfo.stat.ub.es/?page_id=2
The Statistics and Bioinformatics research group has as its main objectives the development of methods and tools to deal with problems appearing in the interface between Statistics and Bioinformatics. We started focusing in DNA microarrays but we are also interested in statistical methods for ''omics'' data integration and next generation sequencing (NGS). Our group collaborates with different research groups in the fields of biology and biomedicine, to whom it offers statistical support for problems which are specifically statistic in nature, such as experimental design or microarray data analysis, and also in more general aspects, such as modeling, analysis or data mining. After a first period of collaboration agreements with the Fundaci�� Vall d''Hebr��n Institut de Recerca we contributed to the creation of the Statistics and Bioinformatics Unit (UEB) which provides statistical and bioinformatical support to VHIR researchers.
Proper citation: University of Barcelona Statistics and Bioinformatics Research Group (RRID:SCR_005704) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 27, 2014. Database containing information on microbial biocatalytic reactions and biodegradation pathways for primarily xenobiotic, chemical compounds. Its goal is to provide information on microbial enzyme-catalyzed reactions that are important for biotechnology. The reactions covered are studied for basic understanding of nature, biocatalysis leading to specialty chemical manufacture, and biodegradation of environmental pollutants. Individual reactions and metabolic pathways are presented with information on the starting and intermediate chemical compounds, the organisms that transform the compounds, the enzymes, and the genes. The present database has been successfully used to teach enzymology and use of biochemical Internet information resources to advanced undergraduate and graduate students, and is being expanded primarily with the help of such students. In addition to reactions and pathways, this database also contains Biochemical Periodic Tables and a Pathway Prediction System. * Search the UM-BBD for compound, enzyme, microorganism, pathway, or BT rule name; chemical formula; chemical structure; CAS Registry Number; or EC code. * Go to Pathways and Metapathways in the UM-BBD * Lists of 203 pathways; 1400 reactions; 1296 compounds; 916 enzymes; 510 microorganism entries; 245 biotransformation rules; 50 organic functional groups; 76 reactions of naphthalene 1,2-dioxygenase; 109 reactions of toluene dioxygenase; Graphical UM-BBD Overview; and Other Graphics (Metapathway and Pathway Maps and Reaction Mechanisms).
Proper citation: UM-BBD (RRID:SCR_005787) Copy
http://bio-bigdata.hrbmu.edu.cn/diseasemeth/
Human disease methylation database. DiseaseMeth version 2.0 is focused on aberrant methylomes of human diseases. Used for understanding of DNA methylation driven human diseases.
Proper citation: DiseaseMeth (RRID:SCR_005942) Copy
The DistiLD database aims to increase the usage of existing genome-wide association studies (GWAS) results by making it easy to query and visualize disease-associated SNPs and genes in their chromosomal context. The database performs three important tasks: # published GWAS are collected from several sources and linked to standardized, international disease codes ICD10 codes) # data from the International HapMap Project are analyzed to define linkage disequilibrium (LD) blocks onto which SNPs and genes are mapped # the web interface makes it easy to query and visualize disease-associated SNPs and genes within LD blocks. Users can query the database by diseases, SNPs or genes. No matter which of the three query modes was used, an intermediate page will be shown listing all the studies that matched the search with a link to the corresponding publication. The user can select either all studies related to a certain disease or one specific study for which to view the related LD blocks. The DistiLD resource integrates information on: * Associations between Single Nucleotide Polymorphisms (SNPs) and diseases from genome-wide association studies (GWAS) * Links between SNPs and genes based on linkage disequilibrium (LD) data from HapMap For convenience, we provide the complete datasets as two (zipped) tab-delimited files. The first file contains GWAS results mapped to LD blocks. The second file contains all SNPs and genes assigned to each LD block.
Proper citation: DistiLD - Diseases and Traits in LD (RRID:SCR_005943) Copy
Ratings or validation data are available for this resource
Portal to interactively visualize genomic data. Provides reference sequences and working draft assemblies for collection of genomes and access to ENCODE and Neanderthal projects. Includes collection of vertebrate and model organism assemblies and annotations, along with suite of tools for viewing, analyzing and downloading data.
Proper citation: UCSC Genome Browser (RRID:SCR_005780) Copy
The Oomycete Molecular Genetics Research Collaboration Network (OMGN) is a network for research collaboration for investigators interested in oomycete molecular genetics and genomics. The goals of the OMGN is to facilitate the integration of these investigators into the community and to further strengthen the cooperative culture of this community. A particular emphasis is placed on training and integrating junior faculty and faculty from institutions under-represented in the U.S. research infrastructure. Because of their economic impact as plant pathogens, molecular, genetic and genomics studies are well advanced in many oomycete species. These organisms have served as lead species for the entire Stramenopiles lineage, a major radiation of crown eukaryotes, distinct from plants, animals and fungi. The oomycete molecular genetics community has a strong culture of collaboration and communication, and sharing of techniques and resources. With the recent blossoming of genetic and genomic tools for oomycetes, many new investigators, from a variety of backgrounds, have become interested in oomycete molecular genetics and genomics. The proposed network is open to all researchers with an interest in oomycete molecular genetics and genomics, either at an experimental or a computational level. Investigators new to the field are always welcome, especially those interested in saprophytes and animal pathogens. Goals of OMGN # Provide training to o��mycete molecular genetics researchers, especially those from smaller institutions, in the use of bioinformatics and genomics resources. # Promote the entry, participation and training of new investigators into the field of o��mycete genomics, particularly junior faculty and faculty from institutions under-represented in the U.S. research infrastructure. # Promote communication and collaboration, and minimize duplication of effort, within the worldwide o��mycete genomics community. # Support an O��mycete Genomics Resources Center to maintain and distribute training and research materials produced by community genomics projects. The network''s activities have been supported by two grants from the NSF Research Collaboration Networks in Biology program.
Proper citation: OMGN (RRID:SCR_005781) Copy
http://www.w3.org/2011/prov/wiki/Main_Page
Working group to support the widespread publication and use of provenance information of Web documents, data, and resources. The Working Group will publish W3C Recommendations that define a language for exchanging provenance information among applications. The Working Group is based on an extensive review and roadmap developed by a prior incubator group. Specifications: * PROV Primer * PROV Ontology * PROV Data Model * PROV Notation * PROV Constraints * PROV Access and Query
Proper citation: W3C Provenance Working Group (RRID:SCR_005938) Copy
One of eight Bioinformatics Resource Centers nationwide providing comprehensive web-based genomics resources including a relational database and web application supporting data storage, annotation, analysis, and information exchange to support scientific research directed at viruses belonging to the Arenaviridae, Bunyaviridae, Filoviridae, Flaviviridae, Paramyxoviridae, Poxviridae, and Togaviridae families. These centers serve the scientific community and conduct basic and applied research on microorganisms selected from the NIH/NIAID Category A, B, and C priority pathogens that are regarded as possible bioterrorist threats or as emerging or re-emerging infectious diseases. The VBRC provides a variety of analytical and visualization tools to aid in the understanding of the available data, including tools for genome annotation, comparative analysis, whole genome alignments, and phylogenetic analysis. Each data release contains the complete genomic sequences for all viral pathogens and related strains that are available for species in the above-named families. In addition to sequence data, the VBRC provides a curation for each virus species, resulting in a searchable, comprehensive mini-review of gene function relating genotype to biological phenotype, with special emphasis on pathogenesis.
Proper citation: VBRC (RRID:SCR_005971) Copy
http://bioconductor.org/packages/devel/bioc/html/SeqGSEA.html
Software package that provides methods for gene set enrichment analysis of high-throughput RNA-Seq data by integrating differential expression and splicing. It uses negative binomial distribution to model read count data, which accounts for sequencing biases and biological variation. Based on permutation tests, statistical significance can also be achieved regarding each gene''s differential expression and splicing, respectively.
Proper citation: SeqGSEA (RRID:SCR_005724) Copy
http://vortex.cs.wayne.edu/projects.htm#Onto-Translate
In the annotation world, the same piece of information can be stored and viewed differently across different databases. For instance, more than one Affymetrix probe ID can refer to the same GenBank sequence (accession number) and more than one nucleotide sequence from GenBank can be grouped in a single UniGene cluster. The result of Onto-Express depends on whether the input list contains Affymetrix probe IDs, GenBank accession numbers or UniGene cluster IDs. The user has to be aware of relations between the different forms of the data in order to interpret correctly the results. Even if the user is aware of the relationships and knows how to convert them, most existing tools allow conversions of individual genes. Onto-Translate is a tool that allows the user to perform easily such translations. Affymetrix probe IDs, etc., translate GO terms into other identifiers like GenBank accession number, Uniprot IDs. User account required. Platform: Online tool
Proper citation: Onto-Translate (RRID:SCR_005725) Copy
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