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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
http://amp.pharm.mssm.edu/Harmonizome/
Web application that allows for searching, visualization, and prediction about genes and proteins. It contains a collection of processed datasets gathered to serve and mine knowledge about genes and proteins from major online resources.
Proper citation: Harmonizome (RRID:SCR_016176) Copy
https://github.com/sorgerlab/ashlar
Software for image processing of cyclic immunofluorescence data. It performs alignment by simultaneous harmonization of layer/adjacency registration.
Proper citation: ASHLAR (RRID:SCR_016266) Copy
https://github.com/lanagarmire/lilikoi
Software tool as an R package for personalized pathway-based classification modeling using metabolomics data. Provides personalized pathway deregulation measurements (PDS scores) and offers a standardized classification model for biomarker prediction.
Proper citation: lilikoi (RRID:SCR_016361) Copy
http://emg.nysbc.org/redmine/projects/leginon/wiki/Leginon_Homepage
System designed for automated collection of images from a transmission electron microscope.
Proper citation: Leginon (RRID:SCR_016731) Copy
https://www.proteinmetrics.com/products/byonic/
Software package for advanced peptide and protein identification by tandem mass spectrometry. Allows to define unlimited number of variable modification type and allows the user to set a separate limit on the number of occurrences of each modification type.
Proper citation: PMI-Byonic (RRID:SCR_016735) Copy
https://github.com/hakyimlab/PrediXcan
Software tool to detect known and novel genes associated with disease traits and provide insights into the mechanism of these associations. Used to test the molecular mechanisms through which genetic variation affects phenotype.
Proper citation: PrediXcan (RRID:SCR_016739) Copy
PILGRM (the platform for interactive learning by genomics results mining) puts advanced supervised analysis techniques applied to enormous gene expression compendia into the hands of bench biologists. This flexible system empowers its users to answer diverse biological questions that are often outside of the scope of common databases in a data-driven manner. This capability allows domain experts to quickly and easily generate hypotheses about biological processes, tissues or diseases of interest. Specifically PILGRM helps biologists generate these hypotheses by analyzing the expression levels of known relevant genes in large compendia of microarray data. PILGRM is for the biologist with a set of proteins relevant to a disease, biological function or tissue of interest who wants to find additional players in that process. It uses a data driven method that provides added value for literature search results by mining compendia of publicly available gene expression datasets using lists of relevant and irrelevant genes (standards). PILGRM produces publication quality PDFs usable as supplementary material to describe the computational approach, standards and datasets. Each PILGRM analysis starts with an important biological question (e.g. What genes are relevant for breast cancer but not mammary tissue in general?). For PILGRM to discover relevant genes, it needs examples of both genes that you would (positive) and would not (negative) find interesting. Lists of these genes are what we call standards and in PILGRM you can build your own standards or you can use standards from common sources that we pre-load for your convenience. PILGRM lets you build your own literature-documented standards so that processes, disease, and tissues that are not well covered in databases of tissue expression, disease, or function can still be used for an analysis.
Proper citation: PILGRM (RRID:SCR_004749) Copy
http://biomedicalcomputationreview.org
Magazine published by Simbios, a National NIH Center for Biomedical Computing, covering the latest research wherever computation, biology, and medicine intersect. In addition to disseminating information about the latest research in biomedical computation, they aim to foster community amongst the wide audience interested in any and all aspects of biomedical computing. Whether you are a long time researcher in this area or new to it, please consider joining those who have already started to participate in Biomedical Computation Review. You are encouraged to: * Write a letter to the editor on any relevant topics * Suggest your favorite topics that should receive more attention * Suggest an idea for a feature article * Propose an idea for an Under the Hood tutorial * Tell us any other way in which we can better serve this community
Proper citation: Biomedical Computation Review (RRID:SCR_004866) Copy
http://www.scandb.org/newinterface/about.html
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. A large-scale database of genetics and genomics data associated to a web-interface and a set of methods and algorithms that can be used for mining the data in it. The database contains two categories of single nucleotide polymorphism (SNP) annotations: # Physical-based annotation where SNPs are categorized according to their position relative to genes (intronic, inter-genic, etc.) and according to linkage disequilibrium (LD) patterns (an inter-genic SNP can be annotated to a gene if it is in LD with variation in the gene). # Functional annotation where SNPs are classified according to their effects on expression levels, i.e. whether they are expression quantitative trait loci (eQTLs) for that gene. SCAN can be utilized in several ways including: (i) queries of the SNP and gene databases; (ii) analysis using the attached tools and algorithms; (iii) downloading files with SNP annotation for various GWA platforms. . eQTL files and reported GWAS from NHGRI may be downloaded., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: SCAN (RRID:SCR_005185) Copy
http://gila.bioengr.uic.edu/snp/toposnp
A topographic database for analyzing non-synonymous SNPs (nsSNPs) that can be mapped onto known 3D structures of proteins. These include disease- associated nsSNPs derived from the Online Mendelian Inheritance in Man (OMIM) database and other nsSNPs derived from dbSNP, a resource at the National Center for Biotechnology Information that catalogs SNPs. TopoSNP further classifies each nsSNP site into three categories based on their geometric location: those located in a surface pocket or an interior void of the protein, those on a convex region or a shallow depressed region, and those that are completely buried in the interior of the protein structure. These unique geometric descriptions provide more detailed mapping of nsSNPs to protein structures. It also includes relative entropy of SNPs calculated from multiple sequence alignment as obtained from the Pfam database (a database of protein families and conserved protein motifs) as well as manually adjusted multiple alignments obtained from ClustalW. These structural and conservational data can be useful for studying whether nsSNPs in coding regions are likely to lead to phenotypic changes. TopoSNP includes an interactive structural visualization web interface, as well as downloadable batch data.
Proper citation: TopoSNP (RRID:SCR_005572) Copy
http://code.google.com/p/lapdftext/
Software that facilitates accurate extraction of text from PDF files of research articles for use in text mining applications. It is intended for both scientists and natural language processing (NLP) engineers interested in getting access to text within specific sections of research articles. The system extracts text blocks from PDF-formatted full-text research articles and classifies them into logical units based on rules that characterize specific sections. The LA-PDFText system focuses only on the textual content of the research articles. The current version of LA-PDFText is a baseline system that extracts text using a three-stage process: * identification of blocks of contiguous text * classification of these blocks into rhetorical categories * extraction of the text from blocks grouped section-wise.
Proper citation: lapdftext (RRID:SCR_006167) Copy
http://www.montana.edu/massspec/index.html
Provides access to mass spectrometers and mass spectrometry expertise. The facility currently maintains the following equipment Waters Synapt-XS Q-IMS-TOF with Waters I-Class UHPLC; Agilent 6538 Q-TOF with Agilent 1290 UHPLC;Agilent 7800 Inductively Coupled Plasma with Laser Ablation (193 nm);Bruker micrOTOF with Agilent 1290 UHPLC; Agilent 6490 Triple Quadrupole Mass Spectrometer; Bruker MALDI Autoflex; Agilent GC-MS; Waters Synapt G2S-i Q-TOF with Ion Mobility.
Proper citation: Montana State University Mass Spectrometry Core Facility (RRID:SCR_012482) Copy
http://lab.rockefeller.edu/chait/
Biomedical technology research center that develops cutting-edge mass spectrometric tools for analyzing peptides and proteins. It makes its software tools developed for data analysis freely available.
Proper citation: National Resource for the Mass Spectrometric Analysis of Biological Macromolecules (RRID:SCR_009007) Copy
Biomedical technology research center that develops and makes available to the scientific community high performance computing algorithms, tools and software to leverage modeling efforts at disparate scales of structural biology, cellular microphysiology and large-scale bioimage processing and analysis, with the goal of advancing understanding of the molecular and cellular organization and functional mechanisms that underlie synaptic signaling and regulation.
Proper citation: National Center for Multiscale Modeling of Biological Systems (RRID:SCR_009005) Copy
Provides high-performance tandem mass spectrometry and proteomics, including multiplexed quantitative comparative analysis of protein and post-translational modifications, and a suite of tools for the analysis of mass spectrometry proteomics data. It provides both scientific and technical expertise and state-of-the-art high-performance, tandem mass spectrometric instrumentation. The facility also provides a service for small molecule analysis. Significant instrumentation in the facility includes three QSTAR quadrupole orthogonal time of flight instruments, and both an LTQ-Orbitrap platform with electron transfer dissociation (ETD) and an LTQ-FT linear ion trap FT-ICR instrument equipped with the ability to perform electron capture dissociation (ECD). The Center also has a 4700 Proteomic Analyzer MALDI tandem time of flight instrument; as well as a QTRAP 5500 hybrid triple quadrupole linear ion trap instrument; and a Thermo Fisher LTQ Orbitrap Velos. Major research focuses within the Center are the analysis of post-translational modifications, including phosphorylation and O-GlcNAcylation and development of methods for quantitative comparative analysis of protein and post-translational modification levels. The program also continues to develop one of the leading suites of tools for analysis of mass spectrometry proteomics data, Protein Prospector. The current web-based release allows unrestricted searching of MS and MSMS data, as well as the ability to perform comparative quantitative analysis of samples using isotopic-labeling reagents. It is the only freely-available web-based resource that allows this type of analysis.
Proper citation: National Bio-Organic Biomedical Mass Spectrometry Resource Center (RRID:SCR_009004) Copy
Facility provides instrumentation and scientific support for single cell analysis and sorting. Routinely performs analysis of both eukaryotic and prokaryotic cells for expression of intracellular and extracellular proteins, cell cycle, cell proliferation, cytokine production, and cell sorting based on expression of cell surface antigen(s) and/or expression of genetically engineered intercellular fluorescent proteins.
Proper citation: West Virginia University Flow Cytometry and Single Cell Core Facility (RRID:SCR_017738) Copy
https://mbim.uams.edu/research-cores/flow-cytometry-core-facility/
Core provides flow cytometry instrumentation and analysis. Instruments include Fortessa, FacsAria and Image Stream.
Proper citation: Arkansas University College of Medicine Flow Cytometry Core Facility (RRID:SCR_017741) Copy
https://www.usd.edu/medicine/basic-biomedical-sciences/proteomics-core
Core provides proteomics services to researchers from South Dakota and the surrounding region to rapidly analyze and identify protein expression patterns in their experimental systems.Develops experimental design, protocols, data analysis and interpretation.Provides consulting and advice in grant proposal, as well as data preparation to be submitted to proteomics journal according to requirements.Offers training in use of common equipment such as scanner, spot cutter, imaging software, technique and protocol issues, and sample preparation.
Proper citation: South Dakota University SD BRIN Proteomics Core Facility (RRID:SCR_017743) Copy
https://www.brown.edu/research/facilities/transgenic-and-gene-targeting/home
MTGTF is to support the investigators in using genetically modified mouse models in Brown University, affiliated hospitals and academic institutions in Rhode Island and other states. Provides services of molecular design and generation of transgenic and knock-out mouse models as well as general advice on use and management of such models. Conventional ES cell gene-targeting system is employed to serve as alternative or to fill the limitations of CRISPR/Cas9 system. Routine services include genotype analysis, sperm or embryo cryopreservation and storage, rederivation, in vitro fertilization (IVF). Other services, such as mouse vasectomy, embryo transfer, colony scale-up, intracytoplasmic sperm injection (ICSI) are also available. New services requiring MTGTF resources can be created through request.
Proper citation: Brown University Transgenic and Gene Targeting Core Facility (RRID:SCR_017690) Copy
Core offers high throughput screening of large chemical libraries of compounds to identify novel chemical entities that target biological system of interest.Provides target identification and validation, assay development, high throughput screening, hit confirmation, data mining and medicinal chemistry to facilitate hit to lead development.
Proper citation: Kansas University at Lawrence High Throughput Screening Laboratory Core Facility (RRID:SCR_017752) Copy
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