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http://harvard.eagle-i.net/i/0000012a-2518-fb6c-5617-794280000000

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 27, 2023. Core provides services: RT PCR service, Gene expression profiling service, Proteomics analysis service, Bioinformatics and Systems Biology analyses, Next Generation Sequencing Service, Affymetrix Human and Mouse Gene 2.0 ST Arrays and 2.1 ST Arrayplates. Core proteomics facility for the Dana-Farber/Harvard Cancer Center. Workflows and algorithms for analysis of next-generation sequencing data including RNA-Seq, ChIP-Seq, Epigenetics-Seq and DNA seq, Comprehensive workflow for analysis of Microbiome sequencing data, Integrated systems biology analysis of transcriptome, miRNA, epigenome, metabolomics and proteomics data. Pipelines: MALDI Tissue imaging and targeted quantitative proteomics.

Proper citation: Beth Israel Deaconess Medical Center Genomics Proteomics Bioinformatics and Systems Biology Center (RRID:SCR_009668) Copy   

•   Source: SciCrunch Registry

http://mbcf.dfci.harvard.edu

Core offers services for genomic next-generation sequencing library preparation, sequencing and analysis applications including RNAseq, ChIPseq, ATACseq, CRISPR screening, whole genome methylation profiling, targeted resequencing, single-cell RNAseq, exome sequencing, and more. Performs bioinformatics analysis such as integration of multi-omics datasets or specialized analyses. Genomics core technology platforms include Illumina NovaSeq6000, NextSeq500s, MiSeqs, MiniSeq. High throughput sample preparation is performed on Beckman Coulter Biomek FX and i7 systems. Low throughput samples are prepared by technical staff.

Proper citation: Dana-Farber Cancer Institute Molecular Biology Core Facility (RRID:SCR_009754) Copy   

•   Source: SciCrunch Registry

http://www.mtu.edu/mcff

Core facility provides tools for imaging, analysis, environmental testing, and micro/nanofabrication. Offers data, expertise, and hands-on training. From advanced materials to environmental systems, MCFF is the hub where discovery meets precision.

Proper citation: Michigan Technological University Materials Characterization and Fabrication Core Facility (RRID:SCR_027872) Copy   

•   Source: SciCrunch Registry

http://nmr.chem.cornell.edu

Core specializes in the analysis of small organic and organometallic analytes. Provides access to mass spectrometers for all.

Proper citation: Cornell University Chemistry MS Core Facility (RRID:SCR_028079) Copy   

•   Source: SciCrunch Registry

https://www.roswellpark.org/shared-resources/biostatistics-statistical-genomics

Core offers services in design, oversight, implementation, analysis, publication, and reporting of scientific studies including articulating study objectives and hypotheses, grant writing, conceiving appropriate cost-effective designs and models for achievement of study objectives, monitoring interim and final analyses, and co-authoring abstracts and manuscripts.

Proper citation: Roswell Park Comprehensive Cancer Center Biostatistics and Statistical Genomics Shared Resource BSGSR Core Facility (RRID:SCR_028371) Copy   

•   Source: SciCrunch Registry

https://www.seattlechildrens.org/research/resources/behavioral-phenotyping-core/

Core dedicated to the protocol driven collection, analysis, and reporting of behavioral data using a blend of classic and innovative assays. Supports neuroscience, psychology, pharmacology, genetics, cancer, and development by providing advanced tools and expertise for the precise measurement and interpretation of behavior.

Proper citation: Seattle Childrens Research Institute Behavioral Phenotyping Core Facility (RRID:SCR_026371) Copy   

•   Source: SciCrunch Registry

https://www.bioconductor.org/packages/release/bioc/html/singleCellTK.html

Software R package provides interface to popular tools for importing, quality control, analysis, and visualization of single cell RNA-seq data. Allows users to integrate tools from various packages at different stages of analysis workflow.

Proper citation: singleCellTK (RRID:SCR_026813) Copy   

•   Source: SciCrunch Registry

http://confocal.uconn.edu

Facility provides training and access to advanced light microscopy systems at an hourly rate. In addition, we are available to consult with and support users at every stage of a project including: experimental design, sample preparation, image acquisition, analysis, and data preparation.

Proper citation: University of Connecticut Advanced Light Microscopy Core Facility (RRID:SCR_027547) Copy   

•   Source: SciCrunch Registry

https://datalab.ucdavis.edu/

Core supports data-enabled research through training, advising, and collaboration in data science, covering topics like research design, data access, analysis, visualization, reproducibility, ethics, and use of tools and methods in the areas of machine learning, bioinformatics, HPC, and open-source software.

Proper citation: University of California Davis DataLab Core Facility (RRID:SCR_028941) Copy   

•   Source: SciCrunch Registry

http://tbi.ci.uchicago.edu/

Project to define a roadmap for diffusion MR imaging of traumatic brain imaging and design an infrastructure to implement the recommendations and tested to ensure feasibility, disseminate results, and facilitate deployment and adoption. The research roadmap and infrastructure development will concentrate on three areas: 1) standardization of diffusion imaging methodology, 2) trial design and patient selection for acute or chronic therapy, and 3) development of multi-center collaborations and repositories for evaluating whether advanced diffusion imaging does improve decision making and TBI patients' outcomes. # DTI MRI reproducability: One of the major areas of investigation in this project is to study the reproducibility of data acquisition and image analysis algorithms. Understanding reproducibility defines a base level of deviation from which scans can be analyzed with statistical significance. As part of this work they are also developing site qualification criteria with the intention of setting limits on the MR system minimal performance for acceptable use in TBI evaluation. # Infrastructure for image storage, analysis and visualization: There is a continuing need to refine and extend software methods for diffusion MRI data analysis and visualization. Not only to translate tools into clinical practice, but also to encourage continuation of the innovation and development of new tools and techniques. To deliver upon these goals they are designing and implementing a storage and computational infrastructure to provide access to shared datasets and intuitive interfaces for analysis and visualization through a variety of tools. A strong emphasis has been placed on providing secure data sharing and the ability to add community defined common data elements. The infrastructure is built upon a Software-as-a-Service model, in which tools are hosted and managed remotely allowing users access through well-defined interfaces. The final service will also facilitate composition or orchestration of workflows composed of different analysis and processing tasks (for example using LONI or XNAT pipelines) with the ultimate goal of providing automated no-click evaluations of diffusion MRI data. # Tool development: The final aspect of this project aims to facilitate and encourage tool development and contribution. By providing access to open datasets, they will create a platform on which tool developers can compare and improve and their tools. When tools are sufficiently mature they can be exposed in the infrastructure mentioned above and used by researchers and other developers.

Proper citation: Diffusion MRI of Traumatic Brain Injury (RRID:SCR_001637) Copy   

•   Source: SciCrunch Registry

https://www.cmtk.org/

A Python-based open source toolkit for magnetic resonance connectome mapping, data management, sharing, visualization and analysis. The toolkit includes the connectome mapper (a full DMRI processing pipeline), a new file format for multi modal data and metadata, and a visualization application.

Proper citation: Connectome Mapping Toolkit (RRID:SCR_001644) Copy   

•   Source: SciCrunch Registry

http://dti-tk.sourceforge.net/pmwiki/pmwiki.php

A spatial normalization and atlas construction toolkit optimized for examining white matter morphometry using DTI data with special care taken to respect the tensorial nature of the data. It implements a state-of-the-art registration algorithm that drives the alignment of white matter (WM) tracts by matching the orientation of the underlying fiber bundle at each voxel. The algorithm has been shown to both improve WM tract alignment and to enhance the power of statistical inference in clinical settings. A 2011 study published in NeuroImage ranks DTI-TK the top-performing tool in its class. Key features include: * open standard-based file IO support: NIfTI format for scalar, vector and tensor image volumes * tool chains for manipulating tensor image volumes: resampling, smoothing, warping, registration & visualization * pipelines for WM morphometry: spatial normalization & atlas construction for population-based studies * built-in cluster-computing support: support for open source Sun Grid Engine (SGE) * Interoperability with other popular DTI tools: AFNI, Camino, FSL & DTIStudio * Interoperability with ITK-SNAP: support multi-modal visualization and segmentation

Proper citation: Diffusion Tensor Imaging ToolKit (RRID:SCR_001642) Copy   

•   Source: SciCrunch Registry

http://neuroimage.usc.edu/brainstorm/

Software as collaborative, open source application dedicated to analysis of brain recordings: MEG, EEG, fNIRS, ECoG, depth electrodes and animal invasive neurophysiology. User-Friendly Application for MEG/EEG Analysis.

Proper citation: Brainstorm (RRID:SCR_001761) Copy   

•   Source: SciCrunch Registry

https://www.bioinformatics.babraham.ac.uk/projects/seqmonk/

Software tool to visualize and analyse high throughput mapped sequence data.

Proper citation: SeqMonk (RRID:SCR_001913) Copy   

•   Source: SciCrunch Registry

http://www.qub.ac.uk/schools/BioimagingCoreTechnologyUnit/NIVTA/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. A pan European network for virtual tissue archiving aimed at supporting clinical trials, biomarker research, tissue microarray analysis and virtual slide based education. NIVTA has state-of-the-art digital scanning systems including an Aperio CS system, Aperio OS system (one of only two currently available in Europe) and a Hamamatsu system with fluorescent scanning capability.

Proper citation: Northern Ireland Virtual Tissue Archive (RRID:SCR_004452) Copy   

•   Source: SciCrunch Registry

http://discovery.hsci.harvard.edu/

An online database of curated cancer stem cell (CSC) experiments coupled to the Galaxy analytical framework. Driven by a need to improve our understanding of molecular processes that are common and unique across cancer stem cells (CSCs), the SCDE allows users to consistently describe, share and compare CSC data at the gene and pathway level. The initial focus has been on carefully curating tissue and cancer stem cell-related experiments from blood, intestine and brain to create a high quality resource containing 53 public studies and 1098 assays. The experimental information is captured and stored in the multi-omics Investigation/Study/Assay (ISA-Tab) format and can be queried in the data repository. A linked Galaxy framework provides a comprehensive, flexible environment populated with novel tools for gene list comparisons against molecular signatures in GeneSigDB and MSigDB, curated experiments in the SCDE and pathways in WikiPathways. Investigation/Study/Assay (ISA) infrastructure is the first general-purpose format and freely available desktop software suite targeted to experimentalists, curators and developers and that: * assists in the reporting and local management of experimental metadata (i.e. sample characteristics, technology and measurement types, sample-to-data relationships) from studies employing one or a combination of technologies; * empowers users to uptake community-defined minimum information checklists and ontologies, where required; * formats studies for submission to a growing number of international public repositories endorsing the tools, currently ENA (genomics), PRIDE (proteomics) and ArrayExpress (transcriptomics). Galaxy allows you to do analyses you cannot do anywhere else without the need to install or download anything. You can analyze multiple alignments, compare genomic annotations, profile metagenomic samples and much much more. Best of all, Galaxy''''s history system provides a complete analyses record that can be shared. Every history is an analysis workflow, which can be used to reproduce the entire experiment. The code for this Galaxy instance is available for download from BitBucket.

Proper citation: Stem Cell Discovery Engine (RRID:SCR_004453) Copy   

•   Source: SciCrunch Registry

http://www.trex.uqam.ca/

A web server dedicated to the reconstruction of phylogenetic trees, reticulation networks and to the inference of horizontal gene transfer (HGT) events.

Proper citation: Tree and reticulogram REConstruction (RRID:SCR_004497) Copy   

•   Source: SciCrunch Registry

https://www.fieldtriptoolbox.org

Software toolbox for analysis of MEG, EEG, and other electrophysiological data. Used by experimental neuroscientists.

Proper citation: FieldTrip (RRID:SCR_004849) Copy   

•   Source: SciCrunch Registry

http://galaxyproject.org/

Open, web-based platform providing bioinformatics tools and services for data intensive genomic research. Platform may be used as a service or installed locally to perform, reproduce, and share complete analyses. Galaxy automatically tracks and manages data provenance and provides support for capturing the context and intent of computational methods. Galaxy Community has created Galaxy instances in many different forms and for many different applications including Galaxy servers, cloud services that support Galaxy instances, and virtual machines and containers that can be easily deployed for your own server.The Galaxy team is a part of BX at Penn State, and the Biology and Mathematics and Computer Science departments at Emory University.Training Infrastructure as a Service (TIaaS) is a service offered by some UseGalaxy servers to specifically support training use cases.

Proper citation: Galaxy (RRID:SCR_006281) Copy   

•   Source: SciCrunch Registry

http://www.uni-koeln.de/med-fak/cgars/

Software package to dissect random from non-random patterns in copy number data and thereby to assess significantly enriched somatic copy number aberrations (SCNA) across a set of tumor specimens or cell lines.

Proper citation: CGARS (RRID:SCR_006404) Copy   

•   Source: SciCrunch Registry