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http://www.ala.org.au/

Online repository of information about Australian plants, animals, and fungi. Development started in 2006. The Commonwealth Scientific and Industrial Research Organisation is organisation significantly involved in development of ALA.

Proper citation: Atlas of Living Australia (RRID:SCR_006467) Copy   

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http://www.informatics.jax.org

International database for laboratory mouse. Data offered by The Jackson Laboratory includes information on integrated genetic, genomic, and biological data. MGI creates and maintains integrated representation of mouse genetic, genomic, expression, and phenotype data and develops reference data set and consensus data views, synthesizes comparative genomic data between mouse and other mammals, maintains set of links and collaborations with other bioinformatics resources, develops and supports analysis and data submission tools, and provides technical support for database users. Projects contributing to this resource are: Mouse Genome Database (MGD) Project, Gene Expression Database (GXD) Project, Mouse Tumor Biology (MTB) Database Project, Gene Ontology (GO) Project at MGI, and MouseCyc Project at MGI.

Proper citation: Mouse Genome Informatics (MGI) (RRID:SCR_006460) Copy   

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http://www.alphaone.ufl.edu/dna_tissue_bank1.html

The Alpha-1 Foundation DNA and Tissue Bank, established in 2000 by the Alpha-1 Foundation, is a repository specifically for medical information (hyperlink to data points) and tissue samples (DNA, plasma, lung/liver) for alpha-1-antitrypsin deficient individuals, their family and friends. The Bank serves the international scientific community. Currently the Bank has the largest collection of DNA in the world for Alpha-1-antitrypsin research studies. The Alpha-1 Foundation has established a Tissue Bank Advisory Committee which includes a wide representation of physicians, ethicists, attorneys, consumers as well as international experts in tissue banking. Collectively this Advisory Committee reviews requests for research. At this time the Bank has over 2400 members who have provided valuable medical and/or tissue samples. For investigators interested in obtaining tissue samples with phenotypes from the Bank, please contact the Alpha-1 Foundation or our research staff at the University of Florida.

Proper citation: University of Florida DNA and Tissue Bank (RRID:SCR_006581) 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://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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http://athina.biol.uoa.gr/orienTM/

A computer software that utilizes an initial definition of transmembrane segments to predict the topology of transmembrane proteins from their sequence. It uses position-specific statistical information for amino acid residues which belong to putative non-transmembrane segments derived from a statistical analysis of non-transmembrane regions of membrane proteins stored in the SwissProt database. Its accuracy compares well with that of other popular existing methods.

Proper citation: orienTM (RRID:SCR_006218) Copy   

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http://blog.f1000.com/

A blog presented by Faculty of 1000 highlighting and linking to the latest, greatest research recommended by F1000. Contributors include F1000 staff, freelance journalists, and scientists. We encourage readers to participate in the conversation via email to suggest topics and contribute guest posts.

Proper citation: Naturally Selected (RRID:SCR_006572) Copy   

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http://www.ebi.ac.uk/thornton-srv/databases/drugport/

DrugPort provides an analysis of the structural information available in the Protein Data Bank (PDB) relating to drug molecules and their protein targets. The drug-target data comes from the DrugBank database. You can search the entries by identifier, test or by protein sequence, or you can use the browse options in the menu on the left.

Proper citation: DrugPort (RRID:SCR_006573) Copy   

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http://bioapps.sabanciuniv.edu/enzyminer/

EnzyMiner automatically identifies the PubMed abstracts that contain information on the impact of a protein level mutation on the stability or the activity of a given enzyme. For querying EnzyMiner, please choose an enzyme from the list and specify if you are interested in disease related abstracts or non-disease related abstracts. For disease related abstracts, the mutation list and direct links to the abstracts will be displayed. For those abstracts that are related to non-diseases, in addition to having the mutation list, the abstracts are also categorized into two groups. These two groups determine whether the mutation has an effect on the enzyme''s stability or functionality. If your target enzyme is not in the list, please write the enzyme name to the query box. We will run the EnzyMiner for the desired enzyme and add the results to our database. EnzyMiner has been developed by Computational Biology Lab of Sabanci University.

Proper citation: Enzyminer. (RRID:SCR_006241) Copy   

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http://panoga.sabanciuniv.edu/

A web server to devise functionally important pathways through the identification of single nucleotide polymorphism (SNP)-targeted genes within these pathways. The strength of the methodology stems from its multidimensional perspective, where evidence from the following five resources is combined: (i) genetic association information obtained through GWAS, (ii) SNP functional information, (iii) protein-protein interaction network, (iv) linkage disequilibrium and (v) biochemical pathways.

Proper citation: PANOGA (RRID:SCR_006242) Copy   

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http://neurodojo.blogspot.it/

A blog by Zen Faulkes, an invertebrate neuroethologist at The University of Texas-Pan American.

Proper citation: NeuroDojo (RRID:SCR_006237) Copy   

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http://neuromarca.com/

A blog about neuromarketing, a research methodology born of the fusion of neuroscience and research techniques of conventional marketing in Spanish by Sergio Monge. If you want to read it in English, Google translate does a good job. A good way to learn about practical applications of neuroscience to a field with little exposure in conventional neuroscience academia. The neuromarketing is a branch of market research that uses biometric measurement systems in their studies (EEG, MRI, galvanic skin response, eye-tracking, heart rate ...). One of the most significant differences with conventional research neuromarketing is not content with the verbal statements of the subjects, but aims to go further, unraveling the effect of the unconscious and emotions in decision-making. The author of Neuromarca is Sergio Monge, Degree in Advertising and Public Relations and PhD in Audiovisual Communication and Advertising from the University of the Basque Country / Euskal Herriko Universitatea. Sergio has experience in the field of Corporate Communications and is familiar with the blogosphere and the Internet communication environment. He currently teaches full time for the UPV / EHU and offers some services such as communications and marketing consultant. The interest of the author of this blog by neuroscience and neuromarketing longstanding but his attendance Neuro Connections conference, held from 5 to 7 febreo 2009 in Krakow (Poland), is the main reason he began writing Neuromarca. The intention is that Neuromarca is a repository of articles in Spanish about neuromarketing, so that could be a reference to the Hispanic blogosphere in this emerging discipline.

Proper citation: Neuromarca (RRID:SCR_006236) Copy   

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http://www.botanical-dermatology-database.info/

BoDD is an electronic re-incarnation of BOTANICAL DERMATOLOGY by John Mitchell & Arthur Rook. This updated on-line version is made available to users with the kind permission of the original authors. The original edition has been digitized by Google Books. Although BoDD is actively being updated, updates are uploaded to the website only at about monthly intervals. A vast body of information collected by the Editor (Richard J. Schmidt PhD) awaits addition to the database. Users should be aware that some of the information that is currently accessible is neither accurate nor up-to-date. None of the information presented in BoDD should be regarded as a recommendation to treat any disease or disorder. The following are databases that are present in BoDD: -Balsaminaceae -Elaeagnaceae -Gelsemiaceae -Gentianaceae / Potaliacaceae -Hydroleaceae -Loganiaceae / Spigeliaceae / Strychnaceae -Martyniaceae -Orobanchaceae -Phrymaceae -Sabiaceae -Tamaricaceae

Proper citation: BoDD (RRID:SCR_006592) Copy   

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http://www.signaling-gateway.org/molecule/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 29,2025. Relational database of all significant published qualitative and quantitative information on cell signaling proteins. The Molecule Pages database was developed with the specific aim of allowing interactions, and indeed whole pathways, to be modeled. The goal is to filter the data to present only validated information. In addition, the Gateway is the home of Signaling Update, which provides a one-stop overview of the latest and hottest research in cell signaling for both the specialist and non-specialist alike.

Proper citation: UCSD-Nature Signaling Gateway Molecule Pages (RRID:SCR_006907) Copy   

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http://python-xy.github.io/

Scientific and engineering development software for numerical computations, data analysis and data visualization based on Python programming language, Qt graphical user interfaces and Spyder interactive scientific development environment. Used to interpreted languages (such as MATLAB or IDL) or compiled languages (C/C++ or Fortran) to switch to Python.

Proper citation: Pythonxy (RRID:SCR_006903) Copy   

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http://gtlinker.cnb.csic.es/

Web application that filters and links enriched output data identifying sets of associated genes and terms, producing metagroups of coherent biological significance. The method uses fuzzy reciprocal linkage between genes and terms to unravel their functional convergence and associations. It can also be accessed through its web service.

Proper citation: GeneTerm Linker (RRID:SCR_006385) Copy   

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http://www.bioinfo.no/tools/TAED

A database of sequence alignments and phylogenetic trees for chordates and embryophytes. The Adaptive Evolution Database (TAED) was first presented as a collection of branches from chordate and embryophyte gene families with fast evolutionary rates mapped onto the NCBI taxonomy (1,2). The original gene families were from the Master Catalog and are proprietary (3). A new version of TAED is now presented as a taxonomic shell together with a gene family database. In addition to multiple sequence alignments and phylogenetic trees for all families of chordate and embryophyte sequences, the ratio of non-synonymous to synonymous nucleotide substitution rates (Ka/Ks) is provided for each branch of every phylogenetic tree. This ratio, when significantly greater than 1, is an indicator of positive selection and potentially a change of function of the encoded protein. With a gene tree to species tree mapping, the branches significantly greater than 1 are collated together in a phylogenetic context. The framework is expandable to incorporate other genomic-scale information in a phylogenetic context. Ultimately, the database is designed both to provide high-quality gene families with multiple sequence alignments and phylogenetic trees for chordates and embryophytes, and to enable asking the question, What makes each species unique at the molecular genomic level?

Proper citation: TAED - The Adaptive Evolution Database (RRID:SCR_006930) Copy   

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http://bioapps.rit.albany.edu/MITOPRED/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. It predicts nuclear-encoded mitochondrial proteins from all eukaryotic species including plants. Prediction is based on the occurrence patterns of Pfam domains (version 16.0) in different cellular locations, amino acid composition and pI value differences between mitochondrial and non-mitochondrial locations. Additionally, you may download MITOPRED predictions for complete proteomes. Re-calculated predictions are instantly accessible for proteomes of Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila, Homo sapiens, Mus musculus and Arabidopsis species as well as all the eukaryotic sequences in the Swiss-Prot and TrEMBL databases. Queries, at different confidence levels, can be made through four distinct options: (i) entering Swiss-Prot/TrEMBL accession numbers; (ii) uploading a local file with such accession numbers; (iii) entering protein sequences; (iv) uploading a local file containing protein sequences in FASTA format. The Mitopred algorithm works based on the differences in the Pfam domain occurrence patters and amino acid composition differences in different cellular compartments. Location specific Pfam domains have been determined from the entire eukaryotic set of Swissprot database. Similarly, differences in the amino acid composition between mitochondrial and non-mitochondrial sequences were pre-calculated. This information is used to calculate location-specific amino acid weights that are used to calculate amino acid score. Similarly, pI average values of the N-terminal 25 residues in different cellular location were also determined. This knowledge-base is accessed by the program during execution.

Proper citation: mitopred (RRID:SCR_006135) Copy   

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http://igs-server.cnrs-mrs.fr/mgdb/Rickettsia/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 18, 2016. Rickettsia are obligate intracellular bacteria living in arthropods. They occasionally cause diseases in humans. To understand their pathogenicity, physiologies and evolutionary mechanisms, RicBase is sequencing different species of Rickettsia. Up to now we have determined the genome sequences of R. conorii, R. felis, R. bellii, R. africae, and R. massiliae. The RicBase aims to organize the genomic data to assist followup studies of Rickettsia. This website contains information on R. conorii and R. prowazekii. A R. conorii and R. prowazekii comparative genome map is also available. Images of genome maps, dendrogram, and sequence alignment allow users to gain a visualization of the diagrams.

Proper citation: Rickettsia Genome Database (RRID:SCR_007102) Copy   

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http://chgr.mc.vanderbilt.edu/page/gist

Software package to test if a marker can account in part for the linkage signal in its region. There are two versions of the software: Windows and Linux/Unix.

Proper citation: Genotype-IBD Sharing Test (RRID:SCR_006257) Copy   

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