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Found 44 result(s)
The Sequence Read Archive stores the raw sequencing data from such sequencing platforms as the Roche 454 GS System, the Illumina Genome Analyzer, the Applied Biosystems SOLiD System, the Helicos Heliscope, and the Complete Genomics. It archives the sequencing data associated with RNA-Seq, ChIP-Seq, Genomic and Transcriptomic assemblies, and 16S ribosomal RNA data.
The Expression Atlas provides information on gene expression patterns under different biological conditions such as a gene knock out, a plant treated with a compound, or in a particular organism part or cell. It includes both microarray and RNA-seq data. The data is re-analysed in-house to detect interesting expression patterns under the conditions of the original experiment. There are two components to the Expression Atlas, the Baseline Atlas and the Differential Atlas. The Baseline Atlas displays information about which gene products are present (and at what abundance) in "normal" conditions (e.g. tissue, cell type). It aims to answer questions such as "which genes are specifically expressed in human kidney?". This component of the Expression Atlas consists of highly-curated and quality-checked RNA-seq experiments from ArrayExpress. It has data for many different animal and plant species. New experiments are added as they become available. The Differential Atlas allows users to identify genes that are up- or down-regulated in a wide variety of different experimental conditions such as yeast mutants, cadmium treated plants, cystic fibrosis or the effect on gene expression of mind-body practice. Both microarray and RNA-seq experiments are included in the Differential Atlas. Experiments are selected from ArrayExpress and groups of samples are manually identified for comparison e.g. those with wild type genotype compared to those with a gene knock out. Each experiment is processed through our in-house differential expression statistical analysis pipeline to identify genes with a high probability of differential expression.
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Since the first discovery of RNA pseudoknots more and many more pseudoknots have been found. However, not all of those pseudoknot data are easy to trace. Sometimes the information is hidden in a publication where the title gives no hint that pseudoknot information is there. This was the first reason that we thought that a general accessible information source for pseudoknots would be handy.
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Datanator is an integrated database of genomic and biochemical data designed to help investigators find data about specific molecules and reactions in specific organisms and specific environments for meta-analyses and mechanistic models. Datanator currently includes metabolite concentrations, RNA modifications and half-lives, protein abundances and modifications, and reaction kinetics integrated from several databases and numerous publications. The Datanator website and REST API provide tools for extracting clouds of data about specific molecules and reactions in specific organisms and specific environments, as well as data about similar molecules and reactions in taxonomically similar organisms.
Pathway Commons is a convenient point of access to biological pathway information collected from public pathway databases. Information is sourced from public pathway databases and is readily searched, visualized, and downloaded. The data is freely available under the license terms of each contributing database.
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NONCODE is an integrated knowledge database dedicated to non-coding RNAs (excluding tRNAs and rRNAs). Now, there are 16 species in NONCODE(human, mouse, cow, rat, chicken, fruitfly, zebrafish, celegans, yeast, Arabidopsis, chimpanzee, gorilla, orangutan, rhesus macaque, opossum and platypus).The source of NONCODE includes literature and other public databases. We searched PubMed using key words ‘ncrna’, ‘noncoding’, ‘non-coding’,‘no code’, ‘non-code’, ‘lncrna’ or ‘lincrna. We retrieved the new identified lncRNAs and their annotation from the Supplementary Material or web site of these articles. Together with the newest data from Ensembl , RefSeq, lncRNAdb and GENCODE were processed through a standard pipeline for each species.
The goal of the Signaling Pathways Project knowledgebase is to allow bench researchers to routinely ask sophisticated questions of the universe of multi-omics data points generated by the cellular signaling community. SPP is dedicated to helping researchers to make sense of the often overwhelming volume of multi-omics information in the field of cellular signaling.
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ALEXA is a microarray design platform for 'alternative expression analysis'. This platform facilitates the design of expression arrays for analysis of mRNA isoforms generated from a single locus by the use of alternative transcription initiation, splicing and polyadenylation sites. We use the term 'ALEXA' to describe a collection of novel genomic methods for 'alternative expression' analysis. 'Alternative expression' refers to the identification and quantification of alternative mRNA transcripts produced by alternative transcript initiation, alternative splicing and alternative polyadenylation. This website provides supplementary materials, source code and other downloads for recent publications describing our studies of alternative expression (AE). Most recently we have developed a method, 'ALEXA-Seq' and associated resources for alternative expression analysis by massively parallel RNA sequencing.
The Protein database is a collection of sequences from several sources, including translations from annotated coding regions in GenBank, RefSeq and TPA, as well as records from SwissProt, PIR, PRF, and PDB. Protein sequences are the fundamental determinants of biological structure and function.
Online Mendelian Inheritance in Animals (OMIA) is a catalogue/compendium of inherited disorders, other (single-locus) traits, and genes in 218 animal species (other than human and mouse and rats, which have their own resources) authored by Professor Frank Nicholas of the University of Sydney, Australia, with help from many people over the years. OMIA information is stored in a database that contains textual information and references, as well as links to relevant PubMed and Gene records at the NCBI, and to OMIM and Ensembl.
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The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), advances life & health sciences by providing open access to a suite of resources, with the aim to translate big data into big discoveries and support worldwide activities in both academia and industry.
BioModels is a repository of mathematical models of biological and biomedical systems. It hosts a vast selection of existing literature-based physiologically and pharmaceutically relevant mechanistic models in standard formats. Our mission is to provide the systems modelling community with reproducible, high-quality, freely-accessible models published in the scientific literature.
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While focused on supporting the scientific community, ATCC activities range widely, from repository-related operations to providing specialized services, conducting in-house R&D and intellectual property management. ATCC serves U.S. and international researchers by characterizing cell lines, bacteria, viruses, fungi and protozoa, as well as developing and evaluating assays and techniques for validating research resources and preserving and distributing biological materials to the public and private sector research communities. Our management philosophy emphasizes customer satisfaction, value addition, cost-effective operations and competitive benchmarking for all areas of our enterprise.
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SILVA is a comprehensive, quality-controlled web resource for up-to-date aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains alongside supplementary online services. In addition to data products, SILVA provides various online tools such as alignment and classification, phylogenetic tree calculation and viewer, probe/primer matching, and an amplicon analysis pipeline. With every full release a curated guide tree is provided that contains the latest taxonomy and nomenclature based on multiple references. SILVA is an ELIXIR Core Data Resource.
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GSA is a data repository specialized for archiving raw sequence reads. It supports data generated from a variety of sequencing platforms ranging from Sanger sequencing machines to single-cell sequencing machines and provides data storing and sharing services free of charge for worldwide scientific communities. In addition to raw sequencing data, GSA also accommodates secondary analyzed files in acceptable formats (like BAM, VCF). Its user-friendly web interfaces simplify data entry and submitted data are roughly organized as two parts, viz., Metadata and File, where the former can be further assorted into BioProject, BioSample, Experiment and Run, and the latter contains raw sequence reads.
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HIstome: The Histone Infobase is a database of human histones, their post-translational modifications and modifying enzymes. HIstome is a combined effort of researchers from two institutions, Advanced Center for Treatment, Research and Education in Cancer (ACTREC), Navi Mumbai and Center of Excellence in Epigenetics, Indian Institute of Science Education and Research (IISER), Pune.
LINCS Data Portal provides access to LINCS data from various sources. The program has six Data and Signature Generation Centers: Drug Toxicity Signature Generation Center, HMS LINCS Center, LINCS Center for Transcriptomics, LINCS Proteomic Characterization Center for Signaling and Epigenetics, MEP LINCS Center, and NeuroLINCS Center.
GeneLab is an interactive, open-access resource where scientists can upload, download, store, search, share, transfer, and analyze omics data from spaceflight and corresponding analogue experiments. Users can explore GeneLab datasets in the Data Repository, analyze data using the Analysis Platform, and create collaborative projects using the Collaborative Workspace. GeneLab promises to facilitate and improve information sharing, foster innovation, and increase the pace of scientific discovery from extremely rare and valuable space biology experiments. Discoveries made using GeneLab have begun and will continue to deepen our understanding of biology, advance the field of genomics, and help to discover cures for diseases, create better diagnostic tools, and ultimately allow astronauts to better withstand the rigors of long-duration spaceflight. GeneLab helps scientists understand how the fundamental building blocks of life itself – DNA, RNA, proteins, and metabolites – change from exposure to microgravity, radiation, and other aspects of the space environment. GeneLab does so by providing fully coordinated epigenomics, genomics, transcriptomics, proteomics, and metabolomics data alongside essential metadata describing each spaceflight and space-relevant experiment. By carefully curating and implementing best practices for data standards, users can combine individual GeneLab datasets to gain new, comprehensive insights about the effects of spaceflight on biology. In this way, GeneLab extends the scientific knowledge gained from each biological experiment conducted in space, allowing scientists from around the world to make novel discoveries and develop new hypotheses from these priceless data.
BBMRI-ERIC is a European research infrastructure for biobanking. We bring together all the main players from the biobanking field – researchers, biobankers, industry, and patients – to boost biomedical research. To that end, we offer quality management services, support with ethical, legal and societal issues, and a number of online tools and software solutions. Ultimately, our goal is to make new treatments possible. The Directory is a tool to share aggregate information about the biobanks that are willing external collaboration. It is based on the MIABIS 2.0 standard, which describes the samples and data in the biobanks at an aggregated level.
The Gene database provides detailed information for known and predicted genes defined by nucleotide sequence or map position. Gene supplies gene-specific connections in the nexus of map, sequence, expression, structure, function, citation, and homology data. Unique identifiers are assigned to genes with defining sequences, genes with known map positions, and genes inferred from phenotypic information. These gene identifiers are used throughout NCBI's databases and tracked through updates of annotation. Gene includes genomes represented by NCBI Reference Sequences (or RefSeqs) and is integrated for indexing and query and retrieval from NCBI's Entrez and E-Utilities systems.