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https://www.ohsu.edu/pharmacokinetics-core

Core for analysis of drugs and their metabolites and bio-molecules such as simple peptides, oligonucleotides, carbohydrates, lipids, fatty acids and steroids. Provides open access to laboratory where users prepare and analyze their own samples by HPLC, GC/MS or LC/MS on equipment maintained by core personnel. Provides analysis of samples including development of analytical methods, sample preparation, and data analysis for clinical trials as well as basic science investigations.

Proper citation: OHSU Bioanalytical Shared Resource Pharmacokinetics Core Facility (RRID:SCR_009963) Copy   

•   Source: SciCrunch Registry

https://www.ohsu.edu/advanced-imaging-research-center/about-advanced-imaging-research-center

Provides magnetic resonance instruments including Siemens 3 Tesla Prisma, Siemens Magnetom 7 Tesla, and Bruker 11.75 Tesla to support research investigating normal physiology, brain development and aging, and disease pathophysiology with high performance non invasive imaging capabilities.

Proper citation: OHSU Advanced Imaging Research Center Core Facility (RRID:SCR_009960) Copy   

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http://harvard.eagle-i.net/i/0000012e-5946-2efe-55da-381e80000000

The Biostatistics Center provides support to MGH investigators, as well as serving as a Coordinating Center for several NIH-supported projects. The Center''s staff includes biostatisticians, physicians, research nurses, data managers, project managers, research assistants, and computing staff.

Proper citation: MGH Biostatistics Center (RRID:SCR_009913) Copy   

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http://ohsu.eagle-i.net/i/0000012a-865d-c25e-048a-d9aa80000000

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on December 6, 2022. Core facility that provides the following services: Consultation on protocol development and design process, Exercise testing service, Dual energy x-ray absorptiometry service. The Bionutrition Unit provides nutrition, body composition, and energy expenditure services. Bionutritionist and research kitchen staff are highly experienced and trained to assist investigators with the design and implementation of research meals, feeding studies, and related research. The Bionutrition Unit also provides a variety of energy expenditure and body composition measurement services using a range of equipment.

Proper citation: Oregon Clinical and Translational Research Institute Bionutrition Unit (RRID:SCR_009995) Copy   

•   Source: SciCrunch Registry

https://www.ohsu.edu/proteomics-shared-resource

Core facility that provides the following services: Protein identification and partial sequencing, Determination of whole protein mass, Targeted SRM analysis of known proteins, Protein quantitation assay, Gel electrophoresis. The OHSU Protemics Shared Resource facility was established to make state-of-the-art mass spectrometry based protein analysis analytical capabilities available to the biomedical research community at OHSU.

Proper citation: OHSU Proteomics Shared Resource Core Facility (RRID:SCR_009991) Copy   

•   Source: SciCrunch Registry

http://ohsu.eagle-i.net/i/0000012b-00c9-007b-79a3-373680000000

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on December 6,2022. Core facility that provides the following services: G-banded karyotyping, Sister chromatid exchange service, Fluorescent in situ hybridization, Chromosome breakage and radial formation analysis, Ploidy/Aneuploidy Assessment, Mitotic index service. A fee-for-service cytogentics laboratory available to genetics researchers to assist in development and execution of cytogenetics experiments for research purposes. Through rigorous standardization of protocols and customized experiment development, the OHSU Research Cytogenetics Core Laboratory provides high quality metaphase and interphase cytogenetic data to the OHSU research community. Services are also available to non-profit and commercial investigators located in Oregon and elsewhere.

Proper citation: OHSU Research Cytogenetics Core Laboratory (RRID:SCR_009992) Copy   

•   Source: SciCrunch Registry

http://xula.eagle-i.net/i/00000135-1fe5-4458-77e4-a45080000000

Core facility that provides the following services: Automated DNA sequencing, Quantitative real-time PCR, Genotyping service, Liquid handling service. The Genomics Core Facility is a core resource of LSU Health Science Center, sponsored jointly by the Cancer Center and Genetics Center. The Facility is committed to providing quality service by fulfilling the needs of the research community in a consistently rapid, dependable, and economical fashion. Services include automated DNA sequencing, using state-of-the-art instrumentation (ABI PRISM 3130XL Genetic Analyzers) and the latest protocols to ensure high quality results at reseasonable prices. The Facility also houses an ABI Prism 7900 HT (a high through-put real-time PCR system) and a Biomek2000 liquid handling robot.

Proper citation: LCRC Genomics Core Facility (RRID:SCR_009906) Copy   

•   Source: SciCrunch Registry

http://xula.eagle-i.net/i/00000135-6375-0806-77e4-a45080000000

Core facility that provides the following services: Probe hybridization, Microarray data analysis. In December 2000, the LSUHSC Program in Gene Therapy in conjunction with the Louisiana Gene Therapy Research Consortium created the Microarray Core to cater to the growing needs of investigators who wanted to perform expression studies. Since that time, our core has helped researchers from around the world process over 3000 samples, resulting in numerous peer-reviewed scientific publications.

Proper citation: LCRC Microarray Core (RRID:SCR_009907) Copy   

•   Source: SciCrunch Registry

http://jsu.eagle-i.net/i/0000012c-1c64-7caa-a830-7bcf80000000

The JHS is the largest single-site longitudinal, population-based, cohort study of 5,302 persons initiated in the fall of 2000 to prospectively investigate the determinants of CVD among African Americans in the Jackson, MS metropolitan statistical area. The JHS investigates the various genotype and phenotype factors that affect high blood pressure, heart disease, strokes, diabetes and other important diseases in African Americans. The primary objective of the Jackson Heart Study is to investigate the causes of cardiovascular disease (CVD) in African Americans to learn how to best prevent this group of diseases in the future. More specific objectives include: 1. Identification of factors, which influence the development, and worsening of CVD in African Americans, with an emphasis on manifestations related to high blood pressure (such as remodeling of the left ventricle of the heart, coronary artery disease, heart failure, stroke and disorders affecting the blood vessels of the kidney). 2. Building research capabilities in minority institutions at the undergraduate and graduate level by developing partnerships between minority and majority institutions and enhancing participation of minority investigators in large-scale epidemiologic studies. 3. Attracting minority students to and preparing them for careers in health sciences.

Proper citation: Jackson Heart Study (RRID:SCR_009902) Copy   

•   Source: SciCrunch Registry

http://xula.eagle-i.net/i/00000135-8260-0cac-a9f8-d64580000000

Core facility that provides the following services: Colony Forming Unit (CFU) Assay, Differentiation assays. Core purpose: To propagate, expand and supply high quality samples of normal mesenchymal stem cells (MSCs) from in vitro cultures with appropriate quality control assurances for use by LCRC investigators who are studying any aspect of MSCs in relationship to cancer.

Proper citation: LCRC Adult Stem Cell Core (RRID:SCR_009903) Copy   

•   Source: SciCrunch Registry

http://www.hematology.org/Publications/Videos/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 18, 2016. ASH's video library includes a number of films produced on various topics, including ASH''s history and award winners, Society programs such as the Clinical Research Training Institute, and a trailer and clips from the hematology documentary Blood Detectives, which aired on Discovery Health. These videos were created for educational purposes, and we encourage members of the hematology community to share them with others.

Proper citation: ASH Video Library (RRID:SCR_005777) Copy   

•   Source: SciCrunch Registry

http://microrna.osu.edu/.UCbase4

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. UCbase & miRfunc is a database of (i) human, mouse and rat microRNAs and (ii) Ultraconserved elements providing information about function, expression and correlation between these classes of non-coding RNAs and the disorders related to their aberrant expression. The genomics interface allows the user to explore where whole-genome collections of miRNAs and UCRs are located with respect to annotation sets such as band, disorders and known genes. The Blast interface provides a web tool for matching miRNAs/UCRs elements against any given sequence and providing specific functional information on the results. 481 Ultraconserved sequences (UCRs) longer than 200 bases were discovered in the genomes of human, mouse and rat. These are DNA sequences showing 100 percent identity among the human, mouse and rat genomes. UCRs are frequently located at genomic regions involved in cancer, differentially expressed in human leukemias and carcinomas and in some instances regulated by microRNAs (miRNAs), the most extensively studied category of non-coding RNAs (ncRNAs). Here we present the first database which links UCRs and miRNAs with the related human disorders and genomic properties.

Proper citation: UCbase & miRfunc: Ultraconserved Sequences and miRNA Funciton Database (RRID:SCR_005771) Copy   

•   Source: SciCrunch Registry

http://www.plexdb.org/plex.php?database=Barley/funcexpression.php

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 11, 2012. FuncExpression is a web-based resource for functional interpretation of large scale genomics data. FuncExpression can be used for the functional comparison of plant, animal, and fungal gene name lists generated from genomics and proteomics experiments. Multiple gene lists can be classified, compared and visualized. FuncExpression supports two way-integration of plant gene functional information and the gene expression data, which allows for further cross-validation with plant microarray data from related experiments at BarleyBase. Platform: Online tool

Proper citation: FuncExpression (RRID:SCR_005773) Copy   

•   Source: SciCrunch Registry

http://www.dbs.ifi.lmu.de/~bundschu/LHGDN.html

A text mining derived database with focus on extracting and classifying gene-disease associations with respect to several biomolecular conditions. It uses a machine learning based algorithm to extract semantic gene-disease relations from a textual source of interest. The semantic gene-disease relations were extracted with F-measures of 78. More specifically, the textual source utilized here originates from Entrez Gene''''s GeneRIF (Gene Reference Into Function) database (Mitchell, et al., 2003). LHGDN was created based on a GeneRIF version from March 31st, 2009, consisting of 414241 phrases. These phrases were further restricted to the organism Homo sapiens, which resulted in a total of 178004 phrases. We benchmark our approach on two different tasks. The first task is the identification of semantic relations between diseases and treatments. The available data set consists of manually annotated PubMed abstracts. The second task is the identification of relations between genes and diseases from a set of concise phrases, so-called GeneRIF (Gene Reference Into Function) phrases. In our experimental setting, we do not assume that the entities are given, as is often the case in previous relation extraction work. Rather the extraction of the entities is solved as a subproblem. Compared with other state-of-the-art approaches, we achieve very competitive results on both data sets. To demonstrate the scalability of our solution, we apply our approach to the complete human GeneRIF database. The resulting gene-disease network contains 34758 semantic associations between 4939 genes and 1745 diseases. The gene-disease network is publicly available as a machine-readable RDF graph. We extend the framework of Conditional Random Fields towards the annotation of semantic relations from text and apply it to the biomedical domain. Our approach is based on a rich set of textual features and achieves a performance that is competitive to leading approaches. The model is quite general and can be extended to handle arbitrary biological entities and relation types. The resulting gene-disease network shows that the GeneRIF database provides a rich knowledge source for text mining.

Proper citation: Literature-derived human gene-disease network (RRID:SCR_005653) Copy   

•   Source: SciCrunch Registry

http://bigg.ucsd.edu/

A knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest.

Proper citation: BiGG Database (RRID:SCR_005809) Copy   

•   Source: SciCrunch Registry

http://the_brain.bwh.harvard.edu/uniprobe/

Database that hosts experimental data from universal protein binding microarray (PBM) experiments (Berger et al., 2006) and their accompanying statistical analyses from prokaryotic and eukaryotic organisms, malarial parasites, yeast, worms, mouse, and human. It provides a centralized resource for accessing comprehensive data on the preferences of proteins for all possible sequence variants ("words") of length k ("k-mers"), as well as position weight matrix (PWM) and graphical sequence logo representations of the k-mer data. The database's web tools include a text-based search, a function for assessing motif similarity between user-entered data and database PWMs, and a function for locating putative binding sites along user-entered nucleotide sequences.

Proper citation: UniPROBE (RRID:SCR_005803) Copy   

•   Source: SciCrunch Registry

http://edwardslab.bmcb.georgetown.edu/downloads/

The Peptide Sequence Database contains putative peptide sequences from human, mouse, rat, and zebrafish. Compressed to eliminate redundancy, these are about 40 fold smaller than a brute force enumeration. Current and old releases are available for download. Each species'' peptide sequence database comprises peptide sequence data from releveant species specific UniGene and IPI clusters, plus all sequences from their consituent EST, mRNA and protein sequence databases, namely RefSeq proteins and mRNAs, UniProt''s SwissProt and TrEMBL, GenBank mRNA, ESTs, and high-throughput cDNAs, HInv-DB, VEGA, EMBL, IPI protein sequences, plus the enumeration of all combinations of UniProt sequence variants, Met loss PTM, and signal peptide cleavages. The README file contains some information about the non amino-acid symbols O (digest site corresponding to a protein N- or C-terminus) and J (no digest sequence join) used in these peptide sequence databases and information about how to configure various search engines to use them. Some search engines handle (very) long sequences badly and in some cases must be patched to use these peptide sequence databases. All search engines supported by the PepArML meta-search engine can (or can be patched to) successfully search these peptide sequence databases.

Proper citation: Peptide Sequence Database (RRID:SCR_005764) Copy   

•   Source: SciCrunch Registry

http://mutationassessor.org/

A web server that predicts the functional impact of amino-acid substitutions in proteins, such as mutations discovered in cancer or nonsynonymous polymorphisms. The functional impact is assessed based on evolutionary conservation of the affected amino acid in protein homologs. The method has been validated on a large set (51k) of disease associated (OMIM) and polymorphic variants., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: MutationAssessor (RRID:SCR_005762) Copy   

•   Source: SciCrunch Registry

http://h-invitational.jp/varygene/

It consists of a Genome Browser, an LD Search System, and the VaryGene 2 system. The Generic Genome Browser is a combination of database and interactive Web page for manipulating and displaying annotations on genomes, while LDSearchSystem is a search system for linkage disequilibrium (LD) bins. VaryGene 2 is a system to search, display, and download our research results on human polymorphism based on publicly available data and annotations of transcripts presented by H-InvDB. VaryGene 2 provides information about single nucleotide polymorphisms (SNPs), deletion-insertion polymorphisms (DIPs), short tandem repeats (STRs), single amino acid repeats (SARs), structural variation (or copy number variations: CNVs), and their relations to the genome, transcripts, and functional domains. Users can search by polymorphisms, transcripts, STRs/SARs, and CNVs.

Proper citation: VarySysDB (RRID:SCR_005880) Copy   

•   Source: SciCrunch Registry

http://indel.bioinfo.sdu.edu.cn/gridsphere/gridsphere

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. Indel Flanking Region Database is an online resource for indels and the flanking regions of proteins in SCOP superfamilies, including amino acid sequences, lengths, locations, secondary structure constitutions, hydrophilicity / hydrophobicity, domain information, 3D structures and so on. It aims at providing a comprehensive dataset for analyzing the qualities of amino acid insertion/deletions(indels), substitutions and the relationship between them. The indels were obtained through the pairwise alignment of homologous structures in SCOP superfamilies. The IndelFR database contains 2,925,017 indels with flanking regions extracted from 373,402 structural alignment pairs of 12,573 non-redundant domains from 1053 superfamilies. IndelFR has already been used for molecular evolution studies and may help to promote future functional studies of indels and their flanking regions.

Proper citation: IndelFR - Indel Flanking Region Database (RRID:SCR_006050) Copy   

•   Source: SciCrunch Registry