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Found 323 result(s)
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<<<!!!<<< This repository is no longer available. >>>!!!>>> The main objective of our work is to understand the pathomechanisms of late onset neurodegenerative disorders such as Huntington's, Parkinson's, Alzheimer's and Machado Joseph disease and to develop causal therapies for them. The disease causing proteins of these illnesses have been identified, but their functions in the unaffected organism are mostly unknown. Here, we have developed a strategy combining library and matrix yeast two-hybrid screens to generate a highly connected PPI network for Huntington's disease (HD).
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The goals of FMGP are to: (i) sequence complete mitochondrial genomes from all major fungal lineages, (ii) infer a robust fungal phylogeny, (iii) define the origin of the fungi, their protistan ancestors, and their specific phylogenetic link to the animals, (iv) investigate mitochondrial gene expression, introns, RNAse P RNA structures, mobile elements.
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During cell cycle, numerous proteins temporally and spatially localized in distinct sub-cellular regions including centrosome (spindle pole in budding yeast), kinetochore/centromere, cleavage furrow/midbody (related or homolog structures in plants and budding yeast called as phragmoplast and bud neck, respectively), telomere and spindle spatially and temporally. These sub-cellular regions play important roles in various biological processes. In this work, we have collected all proteins identified to be localized on kinetochore, centrosome, midbody, telomere and spindle from two fungi (S. cerevisiae and S. pombe) and five animals, including C. elegans, D. melanogaster, X. laevis, M. musculus and H. sapiens based on the rationale of "Seeing is believing" (Bloom K et al., 2005). Through ortholog searches, the proteins potentially localized at these sub-cellular regions were detected in 144 eukaryotes. Then the integrated and searchable database MiCroKiTS - Midbody, Centrosome, Kinetochore, Telomere and Spindle has been established.
The Fungal Genetics Stock Center has preserved and distributed strains of genetically characterized fungi since 1960. The collection includes over 20,000 accessioned strains of classical and genetically engineered mutants of key model, human, and plant pathogenic fungi. These materials are distributed as living stocks to researchers around the world.
The HomoloGene database provides a system for the automated detection of homologs among annotated genes of genomes across multiple species. These homologs are fully documented and organized by homology group. HomoloGene processing uses proteins from input organisms to compare and sequence homologs, mapping back to corresponding DNA sequences.
Human Protein Reference Database (HPRD) has been established by a team of biologists, bioinformaticists and software engineers. This is a joint project between the PandeyLab at Johns Hopkins University, and Institute of Bioinformatics, Bangalore. HPRD is a definitive repository of human proteins. This database should serve as a ready reckoner for researchers in their quest for drug discovery, identification of disease markers and promote biomedical research in general. Human Proteinpedia (www.humanproteinpedia.org) is its associated data portal.
CDC.gov is the Centers for Disease Control and Prevention primary online communication channel. CDC.gov provides users with credible, reliable health information on Data and Statistics, Diseases and Conditions, Emergencies and Disasters, Environmental Health, Healthy Living, Injury, Violence and Safety,Life Stages and Populations, Travelers' Health, Workplace Safety and Health
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>>>!!!<<< The NCI Cancer Models Database, caMOD, was retired on December 24, 2015. Information about many of the mouse models hosted in caMOD was obtained from the Jackson Laboratory Mouse Tumor Biology (MTB) Database and can be accessed through that resource http://tumor.informatics.jax.org/mtbwi/index.do . See caMOD Retirement Announcement https://wiki.nci.nih.gov/display/caMOD/caMOD+Retirement+Announcement >>>>!!<<< Query the Cancer Models database for models submitted by fellow researchers. Retrieve information about the making of models, their genetic description, histopathology, derived cell lines, associated images, carcinogenic agents, and therapeutic trials. Links to associated publications and other resources are provided.
OpenWorm aims to build the first comprehensive computational model of the Caenorhabditis elegans (C. elegans), a microscopic roundworm. With only a thousand cells, it solves basic problems such as feeding, mate-finding and predator avoidance. Despite being extremely well studied in biology, this organism still eludes a deep, principled understanding of its biology. We are using a bottom-up approach, aimed at observing the worm behaviour emerge from a simulation of data derived from scientific experiments carried out over the past decade. To do so we are incorporating the data available in the scientific community into software models. We are engineering Geppetto and Sibernetic, open-source simulation platforms, to be able to run these different models in concert. We are also forging new collaborations with universities and research institutes to collect data that fill in the gaps All the code we produce in the OpenWorm project is Open Source and available on GitHub.
Genome track alignments using GBrowse on this site are featured with: (1) Annotated and predicted genes and transcripts; (2) QTL / SNP Association tracks; (3) OMIA genes; (4) Various SNP Chip tracks; (5) Other mapping fetures or elements that are available.
<<<!!!<<< OFFLINE >>>!!!>>> A recent computer security audit has revealed security flaws in the legacy HapMap site that require NCBI to take it down immediately. We regret the inconvenience, but we are required to do this. That said, NCBI was planning to decommission this site in the near future anyway (although not quite so suddenly), as the 1,000 genomes (1KG) project has established itself as a research standard for population genetics and genomics. NCBI has observed a decline in usage of the HapMap dataset and website with its available resources over the past five years and it has come to the end of its useful life. The International HapMap Project is a multi-country effort to identify and catalog genetic similarities and differences in human beings. Using the information in the HapMap, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. The Project is a collaboration among scientists and funding agencies from Japan, the United Kingdom, Canada, China, Nigeria, and the United States. All of the information generated by the Project will be released into the public domain. The goal of the International HapMap Project is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. By making this information freely available, the Project will help biomedical researchers find genes involved in disease and responses to therapeutic drugs. In the initial phase of the Project, genetic data are being gathered from four populations with African, Asian, and European ancestry. Ongoing interactions with members of these populations are addressing potential ethical issues and providing valuable experience in conducting research with identified populations. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. The Project officially started with a meeting in October 2002 (https://www.genome.gov/10005336/) and is expected to take about three years.
<<<!!!<<< This repository is no longer available. >>>!!!>>> BioVeL is a virtual e-laboratory that supports research on biodiversity issues using large amounts of data from cross-disciplinary sources. BioVeL supports the development and use of workflows to process data. It offers the possibility to either use already made workflows or create own. BioVeL workflows are stored in MyExperiment - Biovel Group http://www.myexperiment.org/groups/643/content. They are underpinned by a range of analytical and data processing functions (generally provided as Web Services or R scripts) to support common biodiversity analysis tasks. You can find the Web Services catalogued in the BiodiversityCatalogue.
TAED is a database of phylogenetically indexed gene families. It contains multiple sequence alignments from MAFFT1, maximum likelihood phylogenetic trees from PhyML2, bootstrap values for each node, dN/dS ratios for each lineage from the free ratios model in PAML3, and labels for each node of speciation or duplication from gene tree/species tree reconciliation using SoftParsMap4. The phylogenetic indexing enables simultaneous viewing of lineages with high dN/dS that occurred along the same species tree branches. Resources from the Protein Data Bank (PDB) and the Kyoto Encyclopedia of Genes and Genomes (KEGG)5, have been incorporated into the TAED analysis to detect substitutions along each branch within the phylogenetic tree and to assess selection within pathways.
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MaxQB stores and displays collections of large proteomics projects and allows joint analysis and comparison. As a first dataset is contains proteome data of 11 different human cell lines. The 11 cell line proteomes together identify proteins expressed from more than half of all human genes. For each protein of interest, expression levels estimated by label-free quantification can be visualized across the cell lines. Similarly, the expression rank order and estimated amount of each protein within each proteome are plotted.
>>>!!!<<< Noticed 26.08.2020: The NCI CBIIT instance of the CGAP no longer exist on this website. The Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer has a new home at the NCI-funded Institute for Systems Biology Cancer Genomics Cloud available at the following location: https://mitelmandatabase.isb-cgc.org >>>!!!<<<
The Cancer Immunome Database (TCIA) provides results of comprehensive immunogenomic analyses of next generation sequencing data (NGS) data for 20 solid cancers from The Cancer Genome Atlas (TCGA) and other datasource. The Cancer Immunome Atlas (TCIA) was developed and is maintained at the Division of Bioinformatics (ICBI). The database can be queried for the gene expression of specific immune-related gene sets, cellular composition of immune infiltrates (characterized using gene set enrichment analyses and deconvolution), neoantigens and cancer-germline antigens, HLA types, and tumor heterogeneity (estimated from cancer cell fractions). Moreover it provides survival analyses for different types immunological parameters. TCIA will be constantly updated with new data and results.
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Genome resource samples of wild animals, particularly those of endangered mammalian and avian species, are very difficult to collect. In Korea, many of these animals such as tigers, leopards, bears, wolves, foxes, gorals, and river otters, are either already extinct, long before the Korean biologists had the opportunity to study them, or are near extinction. Therefore, proposal for a systematic collection and preservation of genetic samples of these precious animals was adopted by Korea Science & Engineering Foundation (KOSEF). As an outcome, Conservation Genome Resource Bank for Korean Wildlife (CGRB; www.cgrb.org) was established in 2002 at the College of Veterinary Medicine, Seoul National University as one of the Special Research Materials Bank supported by the Scientific and Research Infrastructure Building Program of KOSEF. CGRB operates in collaboration with Seoul Grand Park Zoo managed by Seoul Metropolitan Government, and has offices and laboratories at both Seoul National University and Seoul Grand Park, where duplicate samples are maintained, thereby assuring a long-term, safe preservation of the samples. Thus, CGRB is the first example of the collaborative scientific infrastructure program between university and zoo in Korea.
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The Small Molecule Pathway Database (SMPDB) contains small molecule pathways found in humans, which are presented visually. All SMPDB pathways include information on the relevant organs, subcellular compartments, protein cofactors, protein locations, metabolite locations, chemical structures and protein quaternary structures. Accompanying data includes detailed descriptions and references, providing an overview of the pathway, condition or processes depicted in each diagram.
Gene Expression Omnibus: a public functional genomics data repository supporting MIAME-compliant data submissions. Array- and sequence-based data are accepted. Tools are provided to help users query and download experiments and curated gene expression profiles.
<<<!!!<<< This repository is no longer available. >>>!!!>>> The sequencing of several bird genomes and the anticipated sequencing of many more provided the impetus to develop a model organism database devoted to the taxonomic class: Aves. Birds provide model organisms important to the study of neurobiology, immunology, genetics, development, oncology, virology, cardiovascular biology, evolution and a variety of other life sciences. Many bird species are also important to agriculture, providing an enormous worldwide food source worldwide. Genomic approaches are proving invaluable to studying traits that affect meat yield, disease resistance, behavior, and bone development along with many other factors affecting productivity. In this context, BirdBase will serve both biomedical and agricultural researchers.
The Protein Data Bank (PDB) is an archive of experimentally determined three-dimensional structures of biological macromolecules that serves a global community of researchers, educators, and students. The data contained in the archive include atomic coordinates, crystallographic structure factors and NMR experimental data. Aside from coordinates, each deposition also includes the names of molecules, primary and secondary structure information, sequence database references, where appropriate, and ligand and biological assembly information, details about data collection and structure solution, and bibliographic citations. The Worldwide Protein Data Bank (wwPDB) consists of organizations that act as deposition, data processing and distribution centers for PDB data. Members are: RCSB PDB (USA), PDBe (Europe) and PDBj (Japan), and BMRB (USA). The wwPDB's mission is to maintain a single PDB archive of macromolecular structural data that is freely and publicly available to the global community.