Tools   Select Another Resource Report Type

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.disgenet.org

Database and discovery platform containing publicly available collections of genes and variants associated to human diseases. Integrates data from curated repositories, GWAS catalogues, animal models and scientific literature.

Proper citation: DisGeNET (RRID:SCR_006178) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.snpedia.com/index.php/SNPedia

Wiki investigating human genetics including information about the effects of variations in DNA, citing peer-reviewed scientific publications. It is used by Promethease to analyze and help explain your DNA. It is based on a wiki model in order to foster communication about genetic variation and to allow interested community members to help it evolve to become ever more relevant. As the cost of genotyping (and especially of fully determining your own genomic sequence) continues to drop, we''''ll all want to know more - a lot more - about the meaning of these DNA variations and SNPedia will be here to help. SNPedia has been launched to help realize the potential of the Human Genome Project to connect to our daily lives and well-being. For more information see the Wikipedia page, http://en.wikipedia.org/wiki/SNPedia * Download URL: http://www.SNPedia.com/index.php/Bulk * Web Service URL: http://bots.SNPedia.com/api.php

Proper citation: SNPedia (RRID:SCR_006125) Copy   

•   Source: SciCrunch Registry

http://cossmos.slu.edu/

Database to search through the nucleic acid structures from the Protein Data Bank and examine structural motifs, including (a)symmetric internal loops, bulge loops, and hairpin loops. They have compiled over 2,000 three-dimensional structures, which can now be searched using different parameters, including PDB information, experimental technique, sequence, and motif type. RNA secondary structure is important for designing therapeutics, understanding protein-RNA binding and predicting tertiary structure of RNA. Several databases and downloadable programs exist that specialize in the three-dimensional (3D) structure of RNA, but none focus specifically on secondary structural motifs such as internal, bulge and hairpin loops. To create the RNA CoSSMos database, 2156 Protein Data Bank (PDB) files were searched for internal, bulge and hairpin loops, and each loop''''s structural information, including sugar pucker, glycosidic linkage, hydrogen bonding patterns and stacking interactions, was included in the database. False positives were defined, identified and reclassified or omitted from the database to ensure the most accurate results possible. Users can search via general PDB information, experimental parameters, sequence and specific motif and by specific structural parameters in the subquery page after the initial search. Returned results for each search can be viewed individually or a complete set can be downloaded into a spreadsheet to allow for easy comparison. The RNA CoSSMos database is updated weekly.

Proper citation: RNA CoSSMos (RRID:SCR_006120) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://proportal.mit.edu/

ProPortal is a database containing genomic, metagenomic, transcriptomic and field data for the marine cyanobacterium Prochlorococcus. Our goal is to provide a source of cross-referenced data across multiple scales of biological organization--from the genome to the ecosystem--embracing the full diversity of ecotypic variation within this microbial taxon, its sister group, Synechococcus and phage that infect them. The site currently contains the genomes of 13 Prochlorococcus strains, 11 Synechococcus strains and 28 cyanophage strains that infect one or both groups. Cyanobacterial and cyanophage genes are clustered into orthologous groups that can be accessed by keyword search or through a genome browser. Users can also identify orthologous gene clusters shared by cyanobacterial and cyanophage genomes. Gene expression data for Prochlorococcus ecotypes MED4 and MIT9313 allow users to identify genes that are up or downregulated in response to environmental stressors. In addition, the transcriptome in synchronized cells grown on a 24-h light-dark cycle reveals the choreography of gene expression in cells in a ''natural'' state. Metagenomic sequences from the Global Ocean Survey from Prochlorococcus, Synechococcus and phage genomes are archived so users can examine the differences between populations from diverse habitats. Finally, an example of cyanobacterial population data from the field is included.

Proper citation: ProPortal (RRID:SCR_006112) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/bioinformatics/mcmbb/

A web tool used in the discrimination of beta-barrel outer membrane proteins with a Markov chain model. MCMBB is a fast algorithm, which discriminates beta-barrel outer membrane proteins from globular proteins and from alpha-helical membrane proteins. The algorithm is based on a 1st order Markov Chain model, which captures the alternating pattern of hydrophilic-hydrophobic residues occurring in the membrane-spanning beta-strands of beta-barrel outer membrane proteins. The model achieves high accuracy in discriminating outer membrane proteins, since it can discriminate beta-barrel outer membrane with a correct classification rate of 90.08% and the globular proteins with a correct classification rate of 92.67%. When submitting alpha-helical membrane proteins, the method shows an accuracy of 100%. A score greater than zero, indicates that the protein is more likely to be a beta-barrel outer membrane protein, whereas a result lower than zero, indicates that the protein is probable not a beta-barrel. You may enter up to 1000 sequences in Fasta format.

Proper citation: MCMBB (RRID:SCR_006198) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/bioinformatics/waveTM/

A web tool for the prediction of transmembrane segments in alpha-helical membrane proteins. A sliding window of 20 residues is used in order to calculate an average residue hydrophobicity profile, using a hydrophobicity scale. Discrete Wavelet Transform is applied on the average residue hydrophobicity signal and the different frequency coefficients produced are adaptively thresholded so that a denoised signal is reconstructed. A dynamic programming algorithm processes the denoised signal to provide the optimal model for the number, the length and the location of membrane-spanning segments. The end points of the predicted segments are extended to include flanking hydrophobic residues. Topology prediction can also be obtained in conjunction with OrienTM (Liakopoulos et al, 2001). Analysis of a non-redundant test set, provides a ~95% per segment accuracy and ~90% per residue accuracy. Now, you can: * Run waveTM on a sequence * Browse the results obtained with the algorithm * View additional material concerning the hydrophobicity scale

Proper citation: waveTM (RRID:SCR_006199) Copy   

•   Source: SciCrunch Registry