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This colony provides a national resource of rhesus monkeys and their tissues to carry out research benefiting the scientific community. The RMBRR maintains a colony of monkeys that have been derived to be specific pathogen free for members of both the herpes and retrovirus families. Over its history, the RMBRR has developed specialized management techniques, housing facilities and highly trained staff to avail these purposefully bred laboratory models, which are 93% genetically identical to humans, to researchers worldwide. Historically, this animal model has been instrumental in research involving blood classification, polio vaccine development, and drug safety and efficacy while currently they are the preferred model for studying the mechanisms of immunodeficiency diseases. Their susceptibility to Simian Immunodeficiency Virus and their homology to the human major histocompatibility complex (MHC) Class I, II and TCR genes make them valuable in HIV research. They are currently the models of choice for HIV/AIDS vaccine development and study. Other areas of research include atherosclerosis, myocarditis, alcoholism, diabetes, cancer and aging. The overall objectives of this resource are to improve the resources available at the RMBRR and to conduct resource-relevant research that improves both the health of the rhesus colony and its usefulness for studies of human disease. The Resource and Management Core is responsible for providing animal resources, tissues/biological fluids, cell lines, expert advice and research support to NIH extramural and intramural programs, other federal agencies and to private sponsors. The Resource-Related Research Core conducts research to improve the health of the animals maintained with special emphasis on studies that will enhance the usefulness of the rhesus as a model for studies of human disease.

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• SciCrunch
• 14 years ago - by Anonymous

Database of homologous genes from Ensembl organisms, structured under ACNUC sequence database management system. It allows to select sets of homologous genes among species, and to visualize multiple alignments and phylogenetic trees. It is possible to search for orthologous genes in a wide range of taxons. HOMOLENS is particularly useful for comparative sequence analysis, phylogeny and molecular evolution studies. More generally, HOMOLENS gives an overall view of what is known about a peculiar gene family. Note that HOMOLENS is split into two databases on this server: HOMOLENS contains the protein sequences while HOMOLENSDNA contains the nucleotide sequences. Protein sequences of HOMOLENS have been generated by translating the CDS of HOMOLENSDNA and using associated cross-references to generate the annotations.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 31, 2022. The Paris School of Neuroscience (ENP) is a network of outstanding neuroscience laboratories in Paris area, within major universities and research institutes. ENP aims at facilitating graduate training of selected students in the Paris area. It covers all areas of Neuroscience and associated methodologies, from fundamental to clinical and from molecular to cognitive. It brings together a majority of the outstanding teams in Neuroscience in le-de-France region. ENP forms a network of research groups, scientific and technological facilities, and research centers, with recognized expertise in Neuroscience, which is original at the international level. Pre-PhD and PhD programs are open to highly talented and motivated students, who received their undergraduate training outside of France, irrespective of their original disciplines. Pre-PhD > Up to a year of rotations in participating laboratories. This can include a Masters degree. PhD > Three year program (with possible one year extension). Training and Courses > Courses in neuroscience and relate topics ? International Conferences and seminars ? French language courses ? Individual supervision by a tutor and a thesis committee ? Annual retreat with faculty members and guest scientists. Principal activities : -Coordinating the offers of the associated universities to organize an advanced international doctoral training program -Facilitating collaborative efforts and innovative research of the participating laboratories -Attracting outstanding scientists to the le-de-France region and facilitating their setting up in Paris area -Organizing joint activities, including seminars, conferences, summer schools, workshops, symposia, etc.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 12,2023. Database of expression patterns of C. elegans promoter::GFP constructs. A text description of the observed pattern is provided, indicating the stage(s) and tissue(s) in which GFP is expressed. Also available for some strains are the corresponding 2D and 3D images. Investigators may browse the entire list, search by gene name, tissue, stage, and pattern. Search results may be downloaded in .csv and .txt formats. All of the strains in the expression pattern database are displayed in the browse page. The records are organized by gene; information such as locus name, genomic location (WormBase), the presence of images and videos, and the actual expression pattern are shown in a tabular format.

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• SciCrunch
• 17 years ago - by Anonymous

The knot server allows the user to check PDB entries or uploaded structures for knots and to visualize them. The size of a knot is determined by deleting amino acids from both ends. This procedure is, however, not perfect and the resulting size should only be treated as a guideline. Mathematically, knots are only well defined in closed (circular) loops. However, both the N- and C-termini of open proteins are typically located close to the surface of the protein and can be connected unambiguously: We reduce the protein to its backbone and draw two lines outward starting at the termini in the direction of the connection line between the center of mass of the backbone and the respective ends. The two lines are joined by a big loop, and the structure is topologically classified by the determination of its Alexander polynomial. To determine an estimate for the size of the knotted core, we successively delete amino acids from the N-terminus until the protein becomes unknotted. The procedure is repeated at the C-terminus starting with the last N-terminal deletion structure that contained the original knot. For each deletion, the outward-pointing line through the new termini is parallel to the respective lines computed for the full structure. Unfortunately, the size of a knot is not always precisely determined by this procedure, so reported sizes should therefore only be treated as approximate. Sponsors: Knots is funded by MIT.

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• SciCrunch
• 17 years ago - by Anonymous

The aim of the PEROXISOME database (PeroxisomeDB) is to gather, organize and integrate curated information on peroxisomal genes, their encoded proteins, their molecular function and metabolic pathway they belong to, and their related disorders. PeroxisomeDB contains the complete peroxisomal proteome of Homo sapiens (encoded by 85 genes) and Saccharomyces cerevisiae (encoded by 61 genes). Now, we have included 34 new organism genomes with the acquisition of 2426 new peroxisomal homolog proteins. PeroxisomeDB 2.0 integrates the peroxisomal metabolome of whole microbody family by the new incorporation of the glycosome proteomes of trypanosomatids and the glyoxysome proteome of Arabidopsis thaliana. The site also provides a Peroxisome Metabolome of peroxisomal genes and proteins, their molecular interactions and metabolic pathways, tools for comparative genomics, predictive tools. Sponsors: Preoxisome Database is funded by Institut de Gntique et deBiologie Molculaire et Cellulaire.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 19,2019.Database of tertiary structural modeling results of threading assembly refinement (TASSER) method for all 907 G protein-coupled receptors (GPCRs) in human genome. All sequences were collected from GPCR database http://www.gpcr.org/7tm/ and http://www.expasy.org/cgi-bin/lists?7tmrlist.txt. Unlike traditional homology modeling approaches, TASSER modeling does not require solved homologous template structures; moreover, it often refines the structures closer to native. G protein-coupled receptors (GPCRs), encoded by about 5% of human genes, comprise the largest family of integral membrane proteins and act as cell surface receptors responsible for the transduction of endogenous signal into a cellular response. Although tertiary structural information is crucial for function annotation and drug design, there are few experimentally determined GPCR structures. To address this issue, we employ the recently developed threading assembly refinement (TASSER) method to generate structure predictions for all 907 putative GPCRs in the human genome. Unlike traditional homology modeling approaches, TASSER modeling does not require solved homologous template structures; moreover, it often refines the structures closer to native. These features are essential for the comprehensive modeling of all human GPCRs when close homologous templates are absent. Based on a benchmarked confidence score, approximately 820 predicted models should have the correct folds. The majority of GPCR models share the characteristic seven-transmembrane helix topology, but 45 ORFs are predicted to have different structures. This is due to GPCR fragments that are predominantly from extracellular or intracellular domains as well as database annotation errors. Our preliminary validation includes the automated modeling of bovine rhodopsin, the only solved GPCR in the Protein Data Bank. With homologous templates excluded, the final model built by TASSER has a global C(alpha) root-mean-squared deviation from native of 4.6 angstroms, with a root-mean-squared deviation in the transmembrane helix region of 2.1 angstroms. Models of several representative GPCRs are compared with mutagenesis and affinity labeling data, and consistent agreement is demonstrated. Structure clustering of the predicted models shows that GPCRs with similar structures tend to belong to a similar functional class even when their sequences are diverse. These results demonstrate the usefulness and robustness of the in silico models for GPCR functional analysis. Sponsors: GPCR is funded by the University at Buffalo, Buffalo, New York.

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• SciCrunch
• 17 years ago - by Anonymous

The Genetic Analysis Workshops (GAWs) are a collaborative effort among genetic epidemiologists to evaluate and compare statistical genetic methods. For each GAW, topics are chosen that are relevant to current analytical problems in genetic epidemiology, and sets of real or computer-simulated data are distributed to investigators worldwide. Results of analyses are discussed and compared at meetings held in even-numbered years. The GAWs began in 1982 were initially motivated by the development and publication of several new algorithms for statistical genetic analysis, as well as by reports in the literature in which different investigators, using different methods of analysis, had reached contradictory conclusions. The impetus was initially to determine the numerical accuracy of the algorithms, to examine the robustness of the methodologies to violations of assumptions, and finally, to compare the range of conclusions that could be drawn from a single set of data. The Workshops have evolved to include consideration of problems related to analyses of specific complex traits, but the focus has always been on analytical methods. The Workshops provide an opportunity for participants to interact in addressing methodological issues, to test novel methods on the same well-characterized data sets, to compare results and interpretations, and to discuss current problems in genetic analysis. The Workshop discussions are a forum for investigators who are evolving new methods of analysis as well as for those who wish to gain further experience with existing methods. The success of the Workshops is due at least in part to the focus on specific problems and data sets, the informality of sessions, and the requirement that everyone who attends must have made a contribution. Topics are chosen and a small group of organizers is selected by the GAW Advisory Committee. Data sets are assembled, and six or seven months before each GAW, a memo is sent to individuals on the GAW mailing list announcing the availability of the GAW data. Included with the memo is a short description of the data sets and a form for requesting data. The form contains a statement to be signed by any investigator requesting the data, acknowledging that the data are confidential and agreeing not to use them for any purpose other than the Genetic Analysis Workshop without written permission from the data provider(s). Data are distributed by the ftp or CD-ROM or, most recently, on the web, together with a more complete written description of the data sets. Investigators who wish to participate in GAW submit written contributions approximately 6-8 weeks before the Workshop. The GAW Advisory Committee reviews contributions for relevance to the GAW topics. Contributions are assembled and distributed to all participants approximately two weeks before the Workshop. Participation in the GAWs is limited to investigators who (1) submit results of their analyses for presentation at the Workshop, or (2) are data providers, invited speakers or discussants, or Workshop organizers. GAWs are held just before the meetings of the American Society of Human Genetics or the International Genetic Epidemiology Society, at a meeting site nearby. We choose a location that will encourage interaction among participants and permit an intense period of concentrated work. The proceedings of each GAW are published. Proceedings from GAW16 were published in part by Genetic Epidemiology 33(Suppl 1), S1-S110 (2009) and in part by Biomed Central (BMC Proceedings, Volume 3, Supplement 7, 2009). Sponsors: GAW is funded by the Southwest Foundation for Biomedical Research.

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• SciCrunch
• 17 years ago - by Anonymous

Bhairpred server is based on machine learning technique SVM using single sequence information, evolutionary profile, predicted and observed secondary structure (as obtained using Psipred and DSSP), predicted and observed accessibility values (as obtainned from Netasa and DSSP). The methods were trained and tested on dataset of 2880 proteins and their performance was evaluated on dataset of 534 proteins used by Thornton (PNAS, 2002). Best prediction results were obtained with hybrid approach that combined prediction results from evolutionary profile, predicted secondary structure and accessibility.

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• SciCrunch
• 17 years ago - by Anonymous

WebProAnalyst provides web-accessible analysis for scanning the quantitative structure-activity relationships in protein families. It searches for a sequence region, whose substitutions are correlated with variations in the activities of a homologous protein set, the so-called activity modulating sites. WebProAnalyst allows users to search for the key physicochemical characteristics of the sites that affect the changes in protein activities. It enables the building of multiple linear regression and neural networks models that relate these characteristics to protein activities. WebProAnalyst implements multiple linear regression analysis, back propagation neural networks and the Structure-Activity Correlation/Determination Coefficient (SACC/SADC). A back propagation neural network is implemented as a two-layered network, one layer as input, the other as output (Rumelhart et al, 1986). WebProAnalyst uses alignment of amino acid sequences and data on protein activity (pK, Km, ED50, among others). The input data are the numerical values for the physicochemical characteristics of a site in the multiple alignment given by a slide window. The output data are the predicted activity values. The current version of WebProAnalyst handles a single activity for a single protein. The SACC/SADC may be defined as an estimate of the strongest multiple correlation between the physicochemical characteristics of a site in a multiple alignment and protein activities. The SACC/SADC coefficient makes possible the calculation of the possible highest correlation achievable for the quantitative relationship between the physicochemical properties of sites and protein activities. The SACC/SADC is a convenient means for an arrangement of positions by their functional significance. WebProAnalyst outputs a list of multiple alignment positions, the respective correlation values, also regression analysis parameters for the relationships between the amino acid physicochemical characteristics at these positions and the protein activity values.

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• SciCrunch
• 17 years ago - by Anonymous

The GeneSeeker allows you to search across different databases simultaneously, given a known human genetic location and expression/phenotypic pattern. The GeneSeeker returns any found gene names which are located on the specified location and expressed in the specified tissue. To search for more expression location in one search, just enter them in the textbox for the expression location and separate them with logical operators (and, or, not). You can specify as many tissues as you want, the program starts 20 queries simultaneously, and then waits for a query to finish before starting another query, to keep server loads to a minimum. You can also search only for expression, just leave the cytogenetic location fields blank, and do the query. If you only want to look for one cytogenetic location, only fill in the first location field, and the GeneSeeker will search with only this one. Housekeeping genes , found in Swissprot can be excluded, or genes that are to be excluded can be specified. Human chromosome localizations are translated with an oxford-grid to mouse chromosome localizations, and then submitted to the Mgd. Sponsors: GeneSeeker is a service provided by the Centre for Molecular and Biomolecular Informatics (CMBI).

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• SciCrunch
• 17 years ago - by Anonymous

Fluorescent allele-calling software toolkit: a computer software for fully automated microsatellite genotyping. (entry from Genetic Analysis Software)

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• SciCrunch
• 14 years ago - by Anonymous

Center for the study of non-human primates. Its mission is the study and use of non-human primates as models for studies of social and biological interactions and for the discovery of methods of prevention, diagnosis and treatment of diseases that afflict humans. Through the stewardship of three unique facilities—Cayo Santiago Field Station, Sabana Seca Field Station, and the Laboratory of Primate Morphology supports a diverse range of research programs that enhance understanding of primate biology and behavior, with direct applications in biomedical and translational research.

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• SciCrunch
• 17 years ago - by Anonymous

This resource has cataloged a total of 80 human hereditary diseases caused by mutations in protease-coding genes, which implies that more than 10% of the human protease genes are involved in human pathologies. They are classified in three groups: loss of function, gain of function, and an heterogeneous group including non-protease homologs (np), putative proteases, and hedgehog proteins with only autoprocessing activity. Type of inheritance is indicated by R (recessive) or D (dominant).

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• SciCrunch
• 17 years ago - by Anonymous

Griffin (G-protein-receptor interacting feature finding instrument) is a high-throughput system to predict GPCR - G-protein coupling selectively with the input of GPCR sequence and ligand molecular weight. This system consists of two parts: 1) HMM section using family specific multiple alignment of GPCRs, 2) SVM section using physico-chemical feature vectors in GPCR sequence. G-protein coupled receptors (GPCR), which is composed of seven transmembrane helices, play a role as interface of signal transduction. The external stimulation for GPCR, induce the coupling with G-protein (Gi/o, Gq/11, Gs, G12/13) followed by different kinds of signal transduction to inner cell. About half of distributed drugs are intending to control this GPCR - G-protein binding system, and therefore this system is important research target for the development of effective drug. For this purpose, it is necessary to monitor, effectively and comprehensively, of the activation of G-protein by identifying ligand combined with GPCR. Since, at present, it is difficult to construct such biochemical experiment system, if the answers for experimental results can be prepared beforehand by using bioinformatics techniques, large progress is brought to G-protein related drug design. Previous works for predicting GPCR-G protein coupling selectivity are using sequence pattern search, statistical models, and HMM representations showed high sensitivity of predictions. However, there are still no works that can predict with both high sensitivity and specificity. In this work we extracted comprehensively the physico-chemical parameters of each part of ligand, GPCR and G-protein, and choose the parameters which have strong correlation with the coupling selectivity of G-protein. These parameters were put as a feature vector, used for GPCR classification based on SVM.

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• SciCrunch
• 17 years ago - by Anonymous

Isofinder is an algorithm running on the web able to predict isochores at the sequence level. Isochores are long genome segments homogeneous in G+C. The algorithm works by moving a sliding pointer from left to right along the DNA sequence and computing the mean G+C values to the left and to the right of the pointer at each point. Additionally, the program checks whether this significance exceeds a probability threshold. If so, the sequence is cut at this point into two subsequences; otherwise, the sequence remains undivided. The procedure continues recursively for each of the two resulting subsequences created by each cut. This leads to the decomposition of a chromosome sequence into long homogeneous genome regions (LHGRs) with well-defined mean G+C contents, each significantly different from the G+C contents of the adjacent LHGRs. Most LHGRs can be identified with Bernardi''s isochores, given their correlation with biological features such as gene density, SINE and LINE (short, long interspersed repetitive elements) densities, recombination rate or single nucleotide polymorphism variability. The resulting isochore maps are available at http://bioinfo2.ugr.es/isochores/, and also at the UCSC Genome Browser (http://genome.cse.ucsc.edu/). Sponsors: Isofinder is funded by Universidad de Granada, Spain.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 12,2023. An integrated packages of tools for microarray data analysis. GEPAS provides a web-based interface that offers diverse analysis options from the early step of preprocessing (normalization of Affymetrix and two-color microarray experiments and other preprocessing options), to the final step of the functional profiling of the experiment (using Gene Ontology, pathways, PubMed abstracts etc.), which include different possibilities for clustering, gene selection, class prediction and array-comparative genomic hybridization management.

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• SciCrunch
• 17 years ago - by Anonymous

Supplier of xiphophorus (platyfish or swordtails) from pedigreed parental lines, representing variety of species. In addition to supplying strains and providing consultation on husbandry and genetic questions, the XGSC produces custom interspecies hybrids (both first generation F1, and backcross hybrid generation BC1) for a variety of projects.

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• SciCrunch
• 17 years ago - by Anonymous

National consortium of medical research institutions working together to transform the local, regional, and national environment to increase the efficiency and speed of clinical and translational research across the country. Consortium members share a common vision to reduce the time it takes for laboratory discoveries to become treatments for patients, to engage communities in clinical research efforts and to train clinical and translational researchers. This consortium includes 60 medical research institutions located throughout the nation, linking them together to energize the discipline of clinical and translational science. The CTSA consortium has five Strategic Goals: * National Clinical and Translational Research Capability * The Training and Career Development of Clinical and Translational Scientists * Consortium-Wide Collaborations * The Health of our Communities and the Nation * T1 Translational Research

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• SciCrunch
• 17 years ago - by Anonymous

A database of 3D magnetic resonance (MRI) images of fish accessible to scientists, educators and the general public via the web. The Marine Vertebrate Collection at the Scripps Institution of Oceanography provides the majority of the DFL specimens.

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• SciCrunch
• 17 years ago - by Anonymous