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http://www.labspaces.net/DNA

Hi. I''m genegeek (aka Catherine Anderson). I realized during my PostDoc that I preferred learning and explaining new results to doing science so I started a non-traditional career of teaching and outreach. I''ll be using this space to explore public perception of genetics and other cool molecular biology stuff. I hope to add to the great discussions re: new science discoveries and general understanding of genetics. I''ve been running an outreach program and enjoy talking to non-experts about their opinions and understanding. I hope my enthusiasm for the topics can come through the screen. My posts are presented as opinion and commentary and do not represent the views of LabSpaces Productions, LLC, my employer, or my educational institution.

Proper citation: Daring Nucleic Adventures - genegeek (RRID:SCR_005215) Copy   

•   Source: SciCrunch Registry

http://gst.ornl.gov/

We are the Computational Biology and Bioinformatics Group of the Biosciences Division of Oak Ridge National Laboratory. We conduct genetics research and system development in genomic sequencing, computational genome analysis, and computational protein structure analysis. We provide bioinformatics and analytic services and resources to collaborators, predict prospective gene and protein models for analysis, provide user services for the general community, including computer-annotated genomes in Genome Channel. Our collaborators include the Joint Genome Institute, ORNL''s Computer Science and Mathematics Division, the Tennessee Mouse Genome Consortium, the Joint Institute for Biological Sciences, and ORNL''s Genome Science and Technology Graduate Program.

Proper citation: Computational Biology at ORNL (RRID:SCR_005710) Copy   

•   Source: SciCrunch Registry

http://www.compbio.dundee.ac.uk/gotcha/gotcha.php

GOtcha provides a prediction of a set of GO terms that can be associated with a given query sequence. Each term is scored independently and the scores calibrated against reference searches to give an accurate percentage likelihood of correctness. These results can be displayed graphically. Why is GOtcha different to what is already out there and why should you be using it? * GOtcha uses a method where it combines information from many search hits, up to and including E-values that are normally discarded. This gives much better sensitivity than other methods. * GOtcha provides a score for each individual term, not just the leaf term or branch. This allows the discrimination between confident assignments that one would find at a more general level and the more specific terms that one would have lower confidence in. * The scores GOtcha provides are calibrated to give a real estimate of correctness. This is expressed as a percentage, giving a result that non-experts are comfortable in interpreting. * GOtcha provides graphical output that gives an overview of the confidence in, or potential alternatives for, particular GO term assignments. The tool is currently web-based; contact David Martin for details of the standalone version. Platform: Online tool

Proper citation: GOtcha (RRID:SCR_005790) Copy   

•   Source: SciCrunch Registry

http://tabit.ucsd.edu/sdec/

A next-generation web-based application that aims to provide an integrated solution for both visualization and analysis of deep-sequencing data, along with simple access to public datasets.

Proper citation: Systems Transcriptional Activity Reconstruction (RRID:SCR_005622) Copy   

•   Source: SciCrunch Registry

http://igs-server.cnrs-mrs.fr/mgdb/Rickettsia/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 18, 2016. Rickettsia are obligate intracellular bacteria living in arthropods. They occasionally cause diseases in humans. To understand their pathogenicity, physiologies and evolutionary mechanisms, RicBase is sequencing different species of Rickettsia. Up to now we have determined the genome sequences of R. conorii, R. felis, R. bellii, R. africae, and R. massiliae. The RicBase aims to organize the genomic data to assist followup studies of Rickettsia. This website contains information on R. conorii and R. prowazekii. A R. conorii and R. prowazekii comparative genome map is also available. Images of genome maps, dendrogram, and sequence alignment allow users to gain a visualization of the diagrams.

Proper citation: Rickettsia Genome Database (RRID:SCR_007102) Copy   

•   Source: SciCrunch Registry

http://www.athamap.de/

Genome wide map of putative transcription factor binding sites in Arabidopsis thaliana genome.Data in AthaMap is based on published transcription factor (TF) binding specificities available as alignment matrices or experimentally determined single binding sites.Integrated transcriptional and post transcriptional data.Provides web tools for analysis and identification of co-regulated genes. Provides web tools for database assisted identification of combinatorial cis-regulatory elements and the display of highly conserved transcription factor binding sites in Arabidopsis thaliana.

Proper citation: AthaMap (RRID:SCR_006717) Copy   

•   Source: SciCrunch Registry

http://www.stowers-institute.org/research/core/molecular-biology

Core services include DNA sequencing, site directed mutagenesis, genome engineering (TALENs & CRISPRS), plasmid preparations and distributing clones/vectors from in house collections. Supports real time quantitative PCR through instrument training, troubleshooting and experimental design. Stowers researchers also have access to Illumina Next Generation Sequencing technology. Constructs libraries, performs sequencing and assists with high throughput genome sequencing, RNA-seq and ChIP-seq projects. Utilizes liquid handling and colony manipulation robots to automate many of services. Provides automation expertise and collaborate with researchers on custom automation projects.

Proper citation: Stowers Institute for Medical Research Molecular Biology Core Facility (RRID:SCR_017776) Copy   

•   Source: SciCrunch Registry

http://ssom.luc.edu/genomics/

Core provides next-generation sequencing capabilities using Illumina MiSeq. Helps with experimental design, quality control analysis, library preparation, and data analysis. MiSeq desktop sequencer allows to access applications such as targeted gene sequencing, metagenomics, small genome sequencing, targeted gene expression, amplicon sequencing, and HLA typing.MiSeq is capable of delivering up to 15 Gb of output with 25 million sequencing reads and 2x300 basepair read lengths.

Proper citation: Loyola University Genomics Core Facility (RRID:SCR_017857) Copy   

•   Source: SciCrunch Registry

https://med.miami.edu/centers-and-institutes/hihg/research-centers/center-for-genome-technology/biorepository-core

Core provides services and houses samples collected over the last 30 years. Biorepository processes, archives, and retrieves biological samples for genomic research. Offers variety of sample processing options including but not limited to automated DNA extraction using Autogen FLEXSTAR+ instrument, automated DNA/RNA extraction using Qiagen QIASymphony, peripheral blood mononuclear cell (PBMC) isolation, serum, plasma and buffy coat isolation, creation of blood cards, DNA/RNA quantitation and qualitation, whole genome amplification, cell-line lymphoblast immortalization and primary fibroblast tissue culture. Offers sample solutions tos uit customized needs.Services also include DNA/RNA Extraction,Sample archiving, retrieval and allocation,Unique and custom labels printing,DNA/RNA quantitation and qualitation,Tissue culture,Whole genome amplification.

Proper citation: University of Miami Hussman Institute for Human Genomics Biorepository Core Facility (RRID:SCR_017816) Copy   

•   Source: SciCrunch Registry

https://med.miami.edu/centers-and-institutes/hihg/research-centers/center-for-genome-technology/sequencing-core

Core Facility offers services utilizing Illumina Novaseq X Plus, Pacific Biosciences Revio, ONT Promethion, and 10x Genomics platforms. The core has extensive knowledge of DNA/RNA library preparation for short-read, long-read and single cell sequencing. Sample preparation is fully automated on Perkin Elmer robotic workstations and tracked via the Clarity LIMS. Services include, but are not limited to, whole genome, exome and custom capture protocols, as well as, bulk RNAseq, small RNAseq, and single cell RNA sequencing.

Proper citation: University of Miami Hussman Institute for Human Genomics Sequencing Core Facility (RRID:SCR_017828) Copy   

•   Source: SciCrunch Registry

http://gif.biotech.iastate.edu/

Provides help with grant review, information on data management plans,suggestion best practices for bionformatics analyses, advise on experimental design for Next Gen Sequencing (NGS) projects.Services include:Genome assembly and annotation,Transcriptome assembly and annotation,SNP/InDel calling,RNA-Seq analysis,ChiP-seq,Introgression mapping,novel gene discovery,Personalized GBrowse instances for data visualization,Access to high performance computing, Custom big data projects.

Proper citation: Iowa State University Genome Informatics Core Facility (RRID:SCR_017790) Copy   

•   Source: SciCrunch Registry

http://cqls.oregonstate.edu/

Formerly Center for Genome Research and Biocomputing Core Facility. Functions and facilities include services in genomics, functional genomics, genotyping and imaging.Biocomputing facilities with computing infrastructure, which includes managed cloud and shared resources, data analyses and training are customized to individual needs, including genome assembly and annotation, analysis of RNAseq, GBS, and metagenomics data, and GPU-enabled deep learning analyses.

Proper citation: Oregon State University Center for Quantitative Life Sciences Core Facility (RRID:SCR_018373) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/genomes

The EBI genomes pages give access to a large number of complete genomes including bacteria, archaea, viruses, phages, plasmids, viroids and eukaryotes. Methods using whole genome shotgun data are used to gain a large amount of genome coverage for an organism. WGS data for a growing number of organisms are being submitted to DDBJ/EMBL/GenBank. Genome entries have been listed in their appropriate category which may be browsed using the website navigation tool bar on the left. While organelles are all listed in a separate category, any from Eukaryota with chromosome entries are also listed in the Eukaryota page. Within each page, entries are grouped and sorted at the species level with links to the taxonomy page for that species separating each group. Within each species, entries whose source organism has been categorized further are grouped and numbered accordingly. Links are made to: * taxonomy * complete EMBL flatfile * CON files * lists of CON segments * Project * Proteomes pages * FASTA file of Proteins * list of Proteins

Proper citation: EBI Genomes (RRID:SCR_002426) Copy   

•   Source: SciCrunch Registry

http://www.broad.mit.edu/annotation/fungi/fgi/

Produces and analyzes sequence data from fungal organisms that are important to medicine, agriculture and industry. The FGI is a partnership between the Broad Institute and the wider fungal research community, with the selection of target genomes governed by a steering committee of fungal scientists. Organisms are selected for sequencing as part of a cohesive strategy that considers the value of data from each organism, given their role in basic research, health, agriculture and industry, as well as their value in comparative genomics.

Proper citation: Fungal Genome Initiative (RRID:SCR_003169) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.udel.edu/Research/skategenomeproject

Core facility provides a model for collaborative approaches to use specialized resources and expertise in an integrated process. Core builds on the expertise and resources provided by the Bioinformatics Cores of the five northeastern states that form NECC. The Skate Genome Annotation Workshops and Jamborees offer training and opportunities for faculty and students to work with and annotate genome sequences. Workshops include lectures, tutorials and exercises annotating the genome of the little skate, Leucoraja erinacea.

Proper citation: University of Delaware Skate Genome Project (RRID:SCR_005300) Copy   

•   Source: SciCrunch Registry

http://aws.amazon.com/1000genomes/

A dataset containing the full genomic sequence of 1,700 individuals, freely available for research use. The 1000 Genomes Project is an international research effort coordinated by a consortium of 75 companies and organizations to establish the most detailed catalogue of human genetic variation. The project has grown to 200 terabytes of genomic data including DNA sequenced from more than 1,700 individuals that researchers can now access on AWS for use in disease research free of charge. The dataset containing the full genomic sequence of 1,700 individuals is now available to all via Amazon S3. The data can be found at: http://s3.amazonaws.com/1000genomes The 1000 Genomes Project aims to include the genomes of more than 2,662 individuals from 26 populations around the world, and the NIH will continue to add the remaining genome samples to the data collection this year. Public Data Sets on AWS provide a centralized repository of public data hosted on Amazon Simple Storage Service (Amazon S3). The data can be seamlessly accessed from AWS services such Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic MapReduce (Amazon EMR), which provide organizations with the highly scalable compute resources needed to take advantage of these large data collections. AWS is storing the public data sets at no charge to the community. Researchers pay only for the additional AWS resources they need for further processing or analysis of the data. All 200 TB of the latest 1000 Genomes Project data is available in a publicly available Amazon S3 bucket. You can access the data via simple HTTP requests, or take advantage of the AWS SDKs in languages such as Ruby, Java, Python, .NET and PHP. Researchers can use the Amazon EC2 utility computing service to dive into this data without the usual capital investment required to work with data at this scale. AWS also provides a number of orchestration and automation services to help teams make their research available to others to remix and reuse. Making the data available via a bucket in Amazon S3 also means that customers can crunch the information using Hadoop via Amazon Elastic MapReduce, and take advantage of the growing collection of tools for running bioinformatics job flows, such as CloudBurst and Crossbow.

Proper citation: 1000 Genomes Project and AWS (RRID:SCR_008801) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/Projects/Fungi/

Fungal genomes available from the Sanger Institute. Data are accessible in a number of ways; for each organism there is a BLAST server, allowing search of the sequences. Sequences can also be down-loaded directly by FTP. In addition, for those organisms being sequenced using a cosmid approach, finished and annotated cosmids are submitted to EMBL and other public databases.

Proper citation: Fungi Sequencing Projects (RRID:SCR_008524) Copy   

•   Source: SciCrunch Registry

http://www.scripps.edu/florida/technologies/cbs/index.html

Core facility that provides access to genome-wide collections of cDNAs and siRNAs that can be used to interrogate cellular models of signal transduction pathways and phenotypes. Services include cell lines, hit-picking clones and various screening sets, and access to equipment.Provides instruments:Analyst Molecular Devices,Embla Molecular Devices, Envision Perkin Elmer, Platemate Matrix, Tecan M200, Wellmate Matrix.

Proper citation: Scripps Research Institute Florida Cell Based High Throughput Screening Core Facility (RRID:SCR_014877) Copy   

•   Source: SciCrunch Registry

https://www.hgsc.bcm.edu/software/mercury

An automated, flexible, and extensible analysis workflow that provides accurate and reproducible genomic results at scales ranging from individuals to large cohorts. The analysis pipeline is deployed in local hardware and the Amazon Web Services cloud via the DNAnexus platform.

Proper citation: Mercury (RRID:SCR_004231) Copy   

•   Source: SciCrunch Registry

http://oligogenome.stanford.edu/

The Stanford Human OligoGenome Project hosts a database of capture oligonucleotides for conducting high-throughput targeted resequencing of the human genome. This set of capture oligonucleotides covers over 92% of the human genome for build 37 / hg19 and over 99% of the coding regions defined by the Consensus Coding Sequence (CCDS). The capture reaction uses a highly multiplexed approach for selectively circularizing and capturing multiple genomic regions using the in-solution method developed in Natsoulis et al, PLoS One 2011. Combined pools of capture oligonucleotides selectively circularize the genomic DNA target, followed by specific PCR amplification of regions of interest using a universal primer pair common to all of the capture oligonucleotides. Unlike multiplexed PCR methods, selective genomic circularization is capable of efficiently amplifying hundreds of genomic regions simultaneously in multiplex without requiring extensive PCR optimization or producing unwanted side reaction products. Benefits of the selective genomic circularization method are the relative robustness of the technique and low costs of synthesizing standard capture oligonucleotide for selecting genomic targets.

Proper citation: OligoGenome (RRID:SCR_006025) Copy   

•   Source: SciCrunch Registry