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http://www.yeastgenome.org/cgi-bin/GO/goSlimMapper.pl

The GO Slim Mapper (aka GO Term Mapper) maps the specific, granular GO terms used to annotate a list of budding yeast gene products to corresponding more general parent GO slim terms. Uses the SGD GO Slim sets. Three GO Slim sets are available at SGD: * Macromolecular complex terms: protein complex terms from the Cellular Component ontology * Yeast GO-Slim: GO terms that represent the major Biological Processes, Molecular Functions, and Cellular Components in S. cerevisiae * Generic GO-Slim: broad, high level GO terms from the Biological Process and Cellular Component ontologies selected and maintained by the Gene Ontology Consortium (GOC) Platform: Online tool

Proper citation: SGD Gene Ontology Slim Mapper (RRID:SCR_005784) Copy   

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http://www.einstein.yu.edu/centers/ictr/

Patient-derived specimens are essential to research in genomics, proteomics, and biomarkers. We provide banking for biological fluid and tissue specimens as well as human DNA and RNA. We provide secure archival sample storage as well as clinically-annotated specimen biobanks for defined research projects. The core serves the human research blood and tissue banking needs of clinical and translational researchers. Samples can be banked by an individual PI or by a consortium of investigators. All samples are tracked and archived using a secure tracking database, the Einstein-Montefiore Bio-Repository Databank (EM-BRED), http://informatics30.aecom.yu.edu/em-bred/default.aspx. EM-BRED provides qualified investigators with a solution to securely link patient specimens to clinical and pathological data. It consists of a user-friendly query engine that allows for comprehensive specimen search, and ultimately to build clinical annotations of relevance. The facility works under the best practices set out by NCI and ISBER (2006) for collection, storage, and retrieval of human biological materials for research.

Proper citation: Einstein-Montefiore Institute for Clinical and Translational Research Biorepository (RRID:SCR_005297) Copy   

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http://wishart.biology.ualberta.ca/polysearch/index.htm

A web-based tool that supports more than 50 different classes of queries against nearly a dozen different types of text, scientific abstract or bioinformatic databases. The typical query supported by PolySearch is Given X, find all Y''s where X or Y can be diseases, tissues, cell compartments, gene/protein names, SNPs, mutations, drugs and metabolites. PolySearch also exploits a variety of techniques in text mining and information retrieval to identify, highlight and rank informative abstracts, paragraphs or sentences.

Proper citation: PolySearch (RRID:SCR_005291) Copy   

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http://blogs.wsj.com/health/

Health Blog offers news and analysis on health and the business of health. The blog is written by Katherine Hobson and includes contributions from staffers at The Wall Street Journal, WSJ.com and Dow Jones Newswires. A searchable interface allows the user to find topics of interest. Katherine Hobson has been writing about health and business for more than 15 years, including stints covering cancer, nutrition, exercise science, the U.S. economy and the U.K. beer industry.

Proper citation: Wall Street Journal Health Blog (RRID:SCR_004914) Copy   

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http://www.jax.org/grc/index.html

Donate a strain to The Jackson Laboratory Repository. Why donate a strain? * Donating reduces your costs of maintaining strains, lab personnel, shipping and resources. * Each donated strain is cryopreserved, protecting against accidental loss and genetic contamination. * Each donated strain is rederived to a high health status and may be resupplied to donors (up to 3 breeder pairs as long as we have live mice available) * Donating fulfills NIH obligations to share mice. How strain donation works: Strains are submitted by investigators for distribution to the scientific community. All repository strains are cryopreserved. All strains are evaluated monthly by the Genetic Resource Committee (GRC). The GRC is made up of staff scientists and resource managers from The Jackson Laboratory. The GRC recommends which strains are most appropriate to include in the Repository. You will be notified by email after your strain has been reviewed. Donation evaluation criteria * Importance of its current use for research, publication history, and current demand * Importance of its anticipated or potential future use * Difficulty of maintenance relative to scientific value * Existence and reliability of other resources that would ensure its survival * Difficulty of re-creating the strain relative to the time and effort required for its importation and preservation

Proper citation: Donate a strain to The Jackson Laboratory Repository (RRID:SCR_005567) Copy   

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http://www.agbase.msstate.edu/cgi-bin/tools/GOanna.cgi

GOanna is used to find annotations for proteins using a similarity search. The input can be a list of IDs or it can be a list of sequences in FASTA format. GOanna will retrieve the sequences if necessary and conduct the specified BLAST search against a user-specified database of GO annotated proteins. The resulting file contains GO annotations of the top BLAST hits. The sequence alignments are also provided so the user can use these to access the quality of the match. Platform: Online tool

Proper citation: GOanna (RRID:SCR_005684) Copy   

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http://katahdin.mssm.edu/kismeth/revpage.pl

A web-based tool for bisulfite sequencing analysis that was designed to be used with plants, since it considers potential cytosine methylation in any sequence context (CG, CHG, and CHH). It provides a tool for the design of bisulfite primers as well as several tools for the analysis of the bisulfite sequencing results. Kismeth is not limited to data from plants, as it can be used with data from any species.

Proper citation: Kismeth (RRID:SCR_005444) Copy   

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http://neurosphere.wordpress.com/

This blog belongs to me, Dave J Hayes PhD, a Neuroscientist at the University of Ottawa''s Institute of Mental Health Research. My research focuses on the neuroscience of motivation and emotion particularly regarding how brains and people respond to aversive and rewarding things in their environment. A neurosphere is a free-floating group of neural stem cells which can multiply, outside of their natural environment, and retain the ability to differentiate into functional brain cells. I don''t work on neurospheres. However, i like the metaphor of a group of people coming together, outside of their natural environment, through their interest in all things neuro which, incidentally, is everything. The sphere of human thought.

Proper citation: neurosphere (RRID:SCR_005478) Copy   

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http://fairbrother.biomed.brown.edu/spliceman/index.cgi

An online tool that takes a set of DNA sequences with point mutations and returns a ranked list to predict the effects of point mutations on pre-mRNA splicing. The current implementation includes 11 genomes: human, chimp, rhesus, mouse, rat, dog, cat, chicken, guinea pig, frog and zebrafish.

Proper citation: Spliceman (RRID:SCR_005354) Copy   

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http://omniBiomarker.bme.gatech.edu

omniBiomarker is a web-application for analysis of high-throughput -omic data. Its primary function is to identify differentially expressed biomarkers that may be used for diagnostic or prognostic clinical prediction. Currently, omniBiomarker allows users to analyze their data with many different ranking methods simultaneously using a high-performance compute cluster. The next release of omniBiomarker will automatically select the most biologically relevant ranking method based on user input regarding prior knowledge. The omniBiomarker workflow * Data: Gene Expression * Algorithms: Knowledge-Driven Gene Ranking * Differentially expressed Genes * Clinical / Biological Validation * Knowledge: NCI Thesaurus of Cancer, Cancer Gene Index * back to Algorithms

Proper citation: omniBiomarker (RRID:SCR_005750) Copy   

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http://scienceblogs.com/

From climate change to intelligent design, HIV/AIDS to stem cells, science education to space exploration, science is figuring prominently in our discussions of politics, religion, philosophy, business and the arts. New insights and discoveries in neuroscience, theoretical physics and genetics are revolutionizing our understanding of who are are, where we come from and where we''re heading. Launched in January 2006, ScienceBlogs is a portal to this global dialogue, a digital science salon featuring the leading bloggers from a wide array of scientific disciplines. Today, ScienceBlogs is the largest online community dedicated to science. We believe in providing our bloggers with the freedom to exercise their own editorial and creative instincts. We do not edit their work and we do not tell them what to write about. We have selected our 80+ bloggers based on their originality, insight, talent, and dedication and how we think they would contribute to the discussion at ScienceBlogs. Our role, as we see it, is to create and continue to improve this forum for discussion, and to ensure that the rich dialogue that takes place at ScienceBlogs resonates outside the blogosphere. ScienceBlogs is always interested in bringing new contributors into our community. If you''re interested in blogging with us, please fill out our application, and we''ll be in touch.

Proper citation: ScienceBlogs (RRID:SCR_005197) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/SCAR/

A web tool to create, display and manipulate structures of small molecules, proteins and DNA.

Proper citation: SCAR (RRID:SCR_006227) Copy   

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http://athina.biol.uoa.gr/bioinformatics/NON-RED/index.html

A web tool to select biological sequences from a given set, with similarity / homology less than a user-defined level. This web-based application takes as input a set of N sequences and outputs a set of sequences of user-determined redundancy. Initially, the algorithm runs an all-against-all BLAST alignment on the input data set and creates an NxN matrix of pairwise distances defined by the similarity percentages. In the next step, the algorithm removes the sequence with the largest number of neighbors, causing that sequence not to be counted as a neighbor of any other sequence during the next iterations. It then reassesses the number of neighbors of each sequence and repeats the previous step until the sequences left over have no more neighbors. The user can specify the similarity (%) threshold and the minimum coverage length of the alignments. Sequences with a similarity below the threshold or a smaller coverage than the minimum length are not considered to be neighbors.

Proper citation: NON-RED (RRID:SCR_006225) Copy   

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http://athina.biol.uoa.gr/SecStr/

A tool to Predict the Secondary Structure of a protein from its amino acid sequence alone. The SecStr package uses six different secondary structure prediction methods (Nagano, Garnier et al., Burges et al., Chou and Fasman , Lim and Dufton and Hider). The results of those methods are combined into a Joint Prediction Histogram (JPH) as described by Hamodrakas, 1988 and Hamodrakas et al., 1982. As previously mentioned, the SecStr package contains computer programs making use of the secondary structure prediction methods of Nagano, Garnier et al., Burges et al., Chou and Fasman, Lim and Dufton and Hider. These programs were written in Fortran. The results of individual prediction methods are combined as described by Hamodrakas (1988), using a Perl program, to produce joint prediction histograms (JPH), for three types of secondary structure, which may be presented separately on a Java Applet. The output may be given either in text or graphics mode. For the latter a Java capable browser is required.

Proper citation: SecStr (RRID:SCR_006220) Copy   

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http://bioinformatics.biol.uoa.gr/CW-PRED/

A web tool for the prediction of Cell Wall-Anchored Proteins in Gram+ Bacteria. Gram-positive bacteria have surface proteins that are often implicated in virulence. A group of extracellular proteins attached to the cell wall contains an LPXTG-like motif that is target for cleavage and covalent coupling to peptidoglycan by sortase enzymes. A new Hidden Markov Model (HMM), an extension to the HMM model from Litou et al., http://www.ncbi.nlm.nih.gov/pubmed/18464329, was developed for predicting the LPXTG and LPXTG-like cell-wall proteins of Gram-positive bacteria. An analysis of 177 completely sequenced genomes has been performed as well. We identified in total 1456 cell-wall proteins, from which 1283 have the LPXTG motif, 39 the NPXTG motif, 53 have the LPXTA and 81 the LAXTG motif.

Proper citation: CW-PRED (RRID:SCR_006188) Copy   

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http://omicslab.genetics.ac.cn/GOEAST/

Gene Ontology Enrichment Analysis Software Toolkit (GOEAST) is a web based software toolkit providing easy to use, visualizable, comprehensive and unbiased Gene Ontology (GO) analysis for high-throughput experimental results, especially for results from microarray hybridization experiments. The main function of GOEAST is to identify significantly enriched GO terms among give lists of genes using accurate statistical methods. Compared with available GO analysis tools, GOEAST has the following unique features: * GOEAST supports analysis for data from various resources, such as expression data obtained using Affymetrix, illumina, Agilent or customized microarray platforms. GOEAST also supports non-microarray based experimental data. The web-based feature makes GOEAST very user friendly; users only have to provide a list of genes in correct formats. * GOEAST provides visualizable analysis results, by generating graphs exhibiting enriched GO terms as well as their relationships in the whole GO hierarchy. * Note that GOEAST generates separate graph for each of the three GO categories, namely biological process, molecular function and cellular component. * GOEAST allows comparison of results from multiple experiments (see Multi-GOEAST tool). The displayed color of each GO term node in graphs generated by Multi-GOEAST is the combination of different colors used in individual GOEAST analysis. Platform: Online tool

Proper citation: GOEAST - Gene Ontology Enrichment Analysis Software Toolkit (RRID:SCR_006580) Copy   

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https://www.mdanderson.org/research/departments-labs-institutes/programs-centers/michale-e-keeling-center-for-comparative-medicine-and-research/national-research-resources-program.html

SMBRR maintains the only self-sustaining national research resource of laboratory-born squirrel monkeys, their tissues and other biological materials, as well as the expertise to carry out research on this animal. Scientists with NIH grants utilize squirrel monkeys to study many diseases that threaten human health including Alzheimer's disease and other disorders of the central nervous system, drug addiction, malaria, and viral diseases. Center that carries out research on squirrel monkey biology and its research uses. It meets the needs of the biomedical research community in three ways: providing national resource for laboratory-born squirrel monkeys, having active research component that continues to add new information about the biology of the squirrel monkey with a particular emphasis on reproduction and colony management, and acts as a source of expertise for squirrel monkey biology, management and husbandry.

Proper citation: Squirrel Monkey Breeding and Research Resource (RRID:SCR_006291) Copy   

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http://cbl-gorilla.cs.technion.ac.il/

A tool for identifying and visualizing enriched GO terms in ranked lists of genes. It can be run in one of two modes: * Searching for enriched GO terms that appear densely at the top of a ranked list of genes or * Searching for enriched GO terms in a target list of genes compared to a background list of genes.

Proper citation: GOrilla: Gene Ontology Enrichment Analysis and Visualization Tool (RRID:SCR_006848) Copy   

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http://webclu.bio.wzw.tum.de/profcom/

Profiling of Complex Functionality (ProfCom) is a web-based tool for the functional interpretation of a gene list that was identified to be related by experiments. A trait which makes ProfCom a unique tool is an ability to profile enrichments of not only available Gene Ontology (GO) terms but also of complex function. A complex function is constructed as Boolean combination of available GO terms. The complex functions inferred by ProfCom are more specific in comparison to single terms and describe more accurately the functional role of genes. Platform: Online tool

Proper citation: ProfCom - Profiling of complex functionality (RRID:SCR_005797) Copy   

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http://tmbeta-genome.cbrc.jp/TMFunction/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 29,2025. Database of functional residues in alpha-helical and beta-barrel membrane proteins. Each protein is identified with its name and source alongwith the Uniprot code. The protein data bank (PDB) codes are also given for available proteins. Different methods and experimental parameters, for example, affinity, dissociation constant, IC50, activity etc. are given in the database. Further, the database provides the numerical experimental value for each residue (or mutant) in a protein. The experimental data are collected from the literature both by searching the journals as well as with the keyword search at PUBMED. In addition, complete reference is given with journal citation and PMID number. TNFunction is cross-linked with the sequence database, Uniprot, structural database, PDB, and literature database, PubMed. The WWW interface enables users to search data based on various terms with different display options for outputs.

Proper citation: TM Function Database (RRID:SCR_007058) Copy   

•   Source: SciCrunch Registry