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THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 19,2022. Human Gut Microbiome Initiative (HGMI) seeks to provide simply annotated, deep draft genome sequences for 100 cultured representatives of the phylogenetic diversity documented by 16S rRNA surveys of the human gut microbiota. Humans are supra-organisms, composed of 10 times more microbial cells than human cells. Therefore, it seems appropriate to consider ourselves as a composite of many species - human, bacterial, and archaeal - and our genome as an amalgamation of human genes and the genes in ''our'' microbial genomes (''microbiome''). In the same sense, our metabolome can be considered to be a synthesis of co-evolved human and microbial traits. The total number of genes present in the human microbiome likely exceeds the number of our H. sapiens genes by orders of magnitude. Thus, without an understanding of our microbiota and microbiome, it not possible to obtain a complete picture of our genetic diversity and of our normal physiology. Our intestine is home to our largest collections of microbes: bacterial densities in the colon (up to 1 trillion cells/ml of luminal contents) are the highest recorded for any known ecosystem. The vast majority of phylogenetic types in the distal gut microbiota belong to just two divisions (phyla) of the domain Bacteria - the Bacteroidetes and the Firmicutes. Members of eight other divisions have also been identified using culture-independent 16S rRNA gene-based surveys. Metagenomic studies of complex microbial communities residing in our various body habitats are limited by the availability of suitable reference genomes for confident assignment of short sequence reads generated by highly parallel DNA sequencers, and by knowledge of the professions (niches) of community members. Therefore, HGMI, which represents a collaboration between Washington University''s Genome Center and its Center for Genome Sciences, seeks to provide simply annotated, deep draft genome sequences for 100 cultured representatives of the phylogenetic diversity documented by 16S rRNA surveys of the human gut microbiota.

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• SciCrunch
• 17 years ago - by Anonymous

The mission of the Arabidopsis Biological Resource Center (ABRC) is to acquire, preserve and distribute seed and DNA resources that are useful to the Arabidopsis research community. More than 100,000 stocks are shipped annually to researchers in more than 60 countries, and modest fees for stocks are charged. The ABRC database functions and ordering system are incorporated into The Arabidopsis Information Resource (TAIR). Researchers can obtain information about Arabidopsis, perform stock searches, order stocks, and view current and past orders. Sponsors: ABRC is supported by the National Science Foundation under Grant No. 0542034.

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• SciCrunch
• 17 years ago - by Anonymous

Glycoword presents up-to-the-minute glycoscience-related keywords, selected by researchers in various fields of the science and interpreted intelligibly by specialists with expertise on each of the fields in the hope of bringing about a better understanding of the rapidly growing modern glycoscience. The website contains information on the following: -lectin -proteoglycan -glycoprotein -glycolipid -saccharide -glycotechnology -glycopathology -glycogene -structural glycobiology -immunity & sugar chain -nervous system & sugar chain -comparative glycomics and life evolution -glycobiology in plant defense -infection & sugar chain -quality control, trafficking and sorting of glycoproteins -fertilization / development & sugar chain

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 26, 2016. A collection of cDNA, gene and protein records of cytokines deposited in public databases provides various information about the cytokine members of vertebrates in other databases including NCBI GenBank, Swiss-Prot, UniGene, TIGR (The Institute for Genomic Research) Gene Indices, Ensembl, Entrez Gene, Mouse Genome Informatics (MGI) and Rat Genome Database (RGD). It also provides orthologous relationship of cytokine members and includes novel members identified in the databases.

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• SciCrunch
• 17 years ago - by Anonymous

This resource contains an alphabetical listing of the various mice knockout genes according to name. Each of the listing contains the phenotypical information observed when a particular gene is knocked out. Other information, such as papers associated to a particular gene and methodology used to conduct the knockout may also be present.<BR/> This resource contains 314 different knockout genes and provides various navigation tools for easy access.<BR/> Sponsors: This resource portal is supported by FBS.<BR/>

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• SciCrunch
• 17 years ago - by Anonymous

Database as a division of GenBank that contains sequence data and other information on single-pass cDNA sequences, or Expressed Sequence Tags, from a number of organisms.

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• SciCrunch
• 17 years ago - by Anonymous

ARGH is an automated, accurate and scalable method by which acronym-definition pairs can be identified within text. Its primary advantage is in enabling information processing methods to resolve author-defined acronyms, however it also allows an automated creation of a reference work on acronym definitions.<BR/> ARGH has several advantages over manual or semi-automated methods, besides time and effort saved, such as enabling identification of relative frequencies for alternate acronyms and definitions as well as spelling, phrasing and hyphenation variants for a unique acronym-definition pair. It also aids users in identifying acronym/definition variants present in the literature that may not necessarily be in biomedical databases.<BR/> ARGH functions by a set of heuristics to accurately locate and identify the boundaries of acronym-definition pairs was developed and refined in terms of precision and recall on subsets of MEDLINE records. These training sets were gradually increased in size and heuristics re-evaluated to ensure scalability.<BR/> ARGH can be tested on over 12 million MEDLINE records, and it can identify more than 174,000 unique acronyms and their 737,000 associated definitions. Currently, it is the world''s largest and most comprehensive catalog of biomedical acronyms and abbreviations, containing approximately 257,000 out of an estimated 277,000 unique acronyms within MEDLINE.<BR/> Sponsors: ARGH is a service of UT Southwestern eTBLAST team.<BR/>

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, Documented on August 12, 2014. Database that identifies new regulatory elements in untranslated regions of protein-coding genes (5 prime flanks, 5 prime UTRs, introns, 3 prime UTRs and 3 prime flanks). The analyses is focused on genes from metazoan species (essentially vertebrates, insects and nematodes). Information on highly conserved regions (sequences, alignments, annotations, bibliographic references) are compiled. Currently 176 out of 326 detected highly conserved regions (HCRs) have been analyzed and incorporated in the database. You can also access the list of annotated conserved elements and the list of conserved elements that remain to be processed. Their approach is based on comparative sequence analysis, for the identification of phylogenetic footprints.

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• SciCrunch
• 13 years ago - by Anonymous

Alternative splicing essentially increases the diversity of the transcriptome and has important implications for physiology, development and the genesis of diseases. This resource uses a different approach to investigate alternative splicing (instead of the conventional case-by case fashion) and integrates all transcripts derived from a gene into a single splicing graph. ASG is a database of splicing graphs for human genes, using transcript information from various major sources (Ensembl, RefSeq, STACK, TIGR and UniGene). Each transcript corresponds to a path in the graph, and alternative splicing is displayed by bifurcations. This representation preserves the relationships between different splicing variants and allows us to investigate systematically all possible putative transcripts. Web interface allows users to display the splicing graphs, to interactively assemble transcripts and to access their sequences as well as neighboring genomic regions. ASG also provide for each gene, an exhaustive pre-computed catalog of putative transcriptsin total more than 1.2 million sequences. It has found that ~65 of the investigated genes show evidence for alternative splicing, and in 5 of the cases, a single gene might produce over 100 transcripts.

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• SciCrunch
• 17 years ago - by Anonymous

HOVERGEN is a database of homologous vertebrate genes, structured under ACNUC sequence database management system. It allows one to select sets of homologous genes among vertebrate species, and to visualize multiple alignments and phylogenetic trees. HOVERGEN is particularly useful for comparative sequence analysis, phylogeny and molecular evolution studies. More generaly, HOVERGEN gives an overall view of what is known about a peculiar gene family.

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• SciCrunch
• 17 years ago - by Anonymous

A systems biology tool for simulation of kinetic models from a curated model database. JWS Online is both a repository of curated biochemical pathway models and a simulation tool for these models. Users are able to view the models in the database, select a particular model, alter its parameters and perform a simulation on it. JWS Online aims to provide a service to the Systems Biology community by 1) giving access to a database of curated models of biological systems, and 2) allowing the users to run these models in a web browser via an easy to use interface, and 3) helping in reviewing of manuscripts containing kinetic models. In addition to this service role, JWS Online is an important component of an ambitious research initiative: The Silicon Cell. Whereas as a service JWS Online is a repository of published models, in the research activity models are not stored as published but are changed to reflect standardized notation of metabolites and enzymes, and a direct link between model and experimental data is provided.

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• SciCrunch
• 17 years ago - by Anonymous

NASCArrays is the Nottingham Arabidopsis Stock Centre''s microarray database. Currently most of the data is for Arabidopsis thaliana experiments run by the NASC Affymetrix Facility. There are also experiments from other species, and experiments run by other centres too. NASCArrays is an Affymetrix microarray database. It contains free Affymetrix microarray data, and also features a series of tools allowing you to query that data in powerful ways. Most of the data currently comes from NASC''s Affymetrix Service. It also includes data from other sources, notably the AtGenExpress project. They currently distribute over 30,000 tubes of seed a year. There are currently the following data mining tools available. All of these tools allow you to type in a gene(s) of interest, and identify experiments or slides that you might be interested in: -Spot History: This tool allows you to see the pattern of gene expression over all slides in the database. Easily identify slides (and therefore experimental treatments) where genes are highly, lowly, or unusually expressed -Two gene scatter plot: This tool allows you to see the pattern of gene expression over all slides for two genes as a scatter plot. If you are interested in two genes, you can find out if they act in tandem, and highlight slides (and therefore experimental conditions) where these two genes behave in an unusual manner. -Gene Swinger: If you have a gene of interest, this tool will show you which experiment the gene expression varied most -Bulk Gene Download: This tool allows you to download the expression of a list of genes over all experiments. You can get all genes over all experiments (the entire database!) from the Super Bulk Gene Download Sponsors: This is a BBSRC funded consortium to provide services to the Arabidopsis community.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. An integrated software suite for functional analysis of experimental data. The scope of data types includes microarray and SAGE gene expression, SNPs and CGH arrays, proteomics, metabolomics, pathway analysis, Y2H and other custom interactions. MetaCore is based on a proprietary manually curated database of human protein-protein, protein-DNA and protein compound interactions, metabolic and signaling pathways and the effects of bioactive molecules in gene expression.

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• SciCrunch
• 17 years ago - by Anonymous

MetNet database contains information on networks of metabolic and regulatory and interactions in Arabidopsis. This information is based on input from biologists in their area of expertise. Types of interactions in MetNetDB include transcription, translation, protein modification, assembly, allosteric regulation, translocation from one subcellular compartment to another. Other fields describing the interactions are subcellular location, confidence, directionality, references, evidence, and synonyms. Data on entities (DNA, RNA, polypeptides, protein complexes, metabolites) are derived from web databases (gene related databases: TAIR, GO, MapMan/GabiPD; protein related databases: PPDB, AMPDB, AtNoPDB, AraPerox, PLprot, BRENDA; metabolite related databases: ChEBI, PubChem, KEGG, NCI compound library, NIST MS library), in some cases with additional annotation by experts. Network information from MetNetDB can be converted to an XML file by XML Builder. From this XML file, it can be transferred to exploRase, which uses the network in conjunction with statistical analysis of expression data; to Cytoscape/FCM, which finds cycles and pathways in the network, and visualizes and models it in combination with expression data; and to MetNetVR, where the network can be visualized in 3D.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented on March 28, 2013. Resources for teaching biochemistry, including videos, animations and graphics. NetBiochem is intended to be a complete Medical Biochemistry center which can be accessed over a computer network. All of NetBiochem, including text, animations and graphics, can be captured to a local hard drive. There a user can modify it in any way they please. They can run the modified version locally for their own purposes as long as they do not charge anyone any fee for the use of the material. Further, one can use the animations and graphics to illustrate your lectures or other local presentations.

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• SciCrunch
• 17 years ago - by Anonymous

An algorithm that generates lists of genes associated with a gene or one or more disorders. The algorithm can be used in high-throughput screening experiments, can create disease-specific micro-arrays, and can sort the results of gene profiling data. Based on the co-citations of all Medline records, MedGene can retrieve the following relationships: 1. A list of human genes associated with a particular human disease in ranking order 2. A list of human genes associated with multiple human diseases in ranking order 3. A list of human diseases associated with a particular human gene in ranking order 4. A list of human genes associated with a particular human gene in ranking order 5. The sorted gene list from other disease related high-throughput experiments, such as micro-array 6. The sorted gene list from other gene related high-throughput experiments, such as micro-array

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• SciCrunch
• 17 years ago - by Anonymous

This database currently holds E-MAP scores (individual interactions and correlation coefficients) for budding yeast genes involved in the early secretory pathway and chromosome function (including DNA damage and repair, transcriptional control, chromosome segregation and telomere regulation). E-MAPs (Epistatic Mini Array Profiles) are formed by creating and quantifying high-density genetic interaction maps. With this method, observed double mutant colony sizes are compared to those that would be expected from a distribution of typical double mutant colonies of each strain. Each interaction is assigned a score, which indicates the magnitude of the difference from the expected value and the certainty of the score. Negative (or aggravating) scores (&lt; -2.5) correspond to synthetic sick/lethal interactions while positive (or alleviating) scores (&gt; +2.5) corresponds to epistatic or suppressor interactions.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 26, 2016. LINNEA Pathways is a user-friendly comprehensive online resource for gene- or protein-based scientific research. It is based on a total of 248 signaling and metabolic human biological pathway maps created for Invitrogen by GeneGo. The current version of iPath features 225 maps displaying human regulatory and metabolic pathways established in experimental literature produced by MetaCore from GeneGo, Inc. The map objects (proteins, genes, EC functions, and compounds) are connected via metabolic transformations and physical protein interactions, which were assembled by the GeneGo team of experienced annotators, geneticists, and biochemists. The pathways are organized in a vertical fashion following the general signaling path from signaling molecules and membrane receptors, via signal transduction cascades, to transcription factors and their gene targets. Following the natural organization of cellular machinery with highly interconnected pathways and modules, many maps are linked together via hyperlinked box symbols. Such linkage allows the reconstruction of a big picture view of human cell biology., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

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• SciCrunch
• 17 years ago - by Anonymous

ITFP is an integrated transcription factor (TF) platform, which included abundant TFs and targets message of mammalian. Support vector machine (SVM) algorithm combined with error-correcting output coding (ECOC) algorithm was utilized to identify and classify transcription factor from protein sequence of Human, Mouse and Rat. For transcription factor targets, a reverse engineering method named ARACNE was used to derive potential interaction pairs between transcription factor and downstream regulated gene from Human, Mouse and Rat gene expression profile data. Detailed information of gene expression profile data can be found in help page. Moreover, all data provided by the platform is free for non-commercial users and can be downloaded through links on help page.

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• SciCrunch
• 17 years ago - by Anonymous

iRefWeb is an interface to a relational database containing the latest build of the interaction Reference Index (iRefIndex) which integrates protein interaction data from nine different interaction databases: BioGRID, BIND, CORUM, DIP, HPRD, INTACT, MINT, MPPI, MPACT and OPHID. Integration is achieved through a rigorously documented procedure for mapping protein IDs across databases, enabling systematic backtracking of the links used to establish the identity of the interaction partners. The iRefWeb interface groups interaction records from the different databases into a single non-redundant view. In particular iRefWeb facilitates comparing interaction records as seen by the various source databases relative to the PubMeds they were annotated from. iRefWeb is one of several views of the iRefIndex resource. Data are also available in a tab-delimited plain-text format (PSI-MITAB) as well as planned releases of a PSI-XML formatted version and a Cytoscape plugin. Further details about the iRefIndex project as well as data downloads are available from here . The method used to build iRefIndex is described in a recent publication.

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• SciCrunch
• 17 years ago - by Anonymous