Curator Dashboard

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Core facility that provides the following services: Clinical data management, Project operations and compliance support, Custom database application development, Research technology support, Proposal development service. The Clinical Research Computing Unit (CRCU) is a designated core research facility within Penn Medicine, specializing in clinical research informatics (CRI) collaboration and research IT services with a growing number of clinical and translational research investigators at Penn. The CRCU currently supports 58 funded projects, valued at more than $336 M (total costs, all years) to Penn. Although situated within the Center for Clinical Epidemiology and Biostatistics (CCEB), the CRCU supports an increasing volume of its research portfolio led by PIs external to the CCEB. This year the total value of these research programs was $ 243 M, so that the proportion attributable to PIs external to CCEB exceeded 70% ($243 M / $336 M = 72%). Established originally on April 1, 1997, within the Biostatistics Unit of the Center for Clinical Epidemiology and Biostatistics (CCEB) at the University of Pennsylvania School of Medicine, the primary foci were to develop a research computing base for the new program in Biostatistics, as well as to create the capacity and resources to compete successfully for data coordinating centers (DCCs) of federally funded, large-scale, multi center clinical trials, and epidemiological studies. These technology resources also permitted CCEB faculty and staff to provide essential collaborative CRI support for Penn investigators throughout the wide array of basic science and clinical departments, centers, and institutes, thus enhancing their likelihood of funding success. On July 1, 2002, the CRCU restructured its operations and expanded its focus in response to the overall research project growth within the CCEB and the University. The CRCU, as an organizational unit, moved from within the Biostatistics Unit of the CCEB to a CCEB-wide organizational service center for both the Biostatistics and Clinical Epidemiology units. With this restructuring, the CRCU now has two faculty co-directors; one representing each of the CCEB units. The faculty directors ensure that the overall strategy and goals of the service center are aligned with the overall goals of the CCEB, as well as Penn Medicine. In 2005, the leadership model was expanded with the appointment of four (4) Directors of Operations, each of whom report directly to the faculty directors and manage a specialty sub-unit of staff to more effectively coordinate the evolving complexities of the more than 58 sponsored project teams. The original two (2) Senior Directors now focus their leadership efforts on technology infrastructure, new methodologies, special projects and fostering strategic collaborations with other Penn departments, commercial vendors, and other institutions. The University of Pennsylvania aspires to excellence in all domains. The CRCU embraces these ideals, as it partners with faculty and staff to conduct biomedical, behavioral, clinical and translational biomedical research at the highest levels of excellence. Advances in healthcare and improvements in quality of life through research depend on thoughtful science and uncompromising integrity in the collection and handling of information. The CRCU excels in the support of biomedical and clinical research by providing expertise in all facets of research information management, and by understanding the regulatory and cultural environments in which research is conducted. The CRCU fosters collaborative relationships with investigators in the CCEB, other Centers and Institutes throughout the School of Medicine, and across the University, to take an active partnership role in meeting their research goals. The CRCU is committed to continuous improvement in the expertise offered and the services provided, through an emphasis on education and training for staff and through the use of leading technologies and creative solutions.

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• SciCrunch
• 13 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Core facility that provides the following services: Maintenance of transgenic or mutant zebrafish lines, Zebrafish research training, Zebrafish embryo supply service. The CDB Zebrafish Core facility provides services and training to Penn faculty interested in using the zebrafish model system as part of their research program.

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• SciCrunch
• 13 years ago - by Anonymous

A basic fastq compressor, designed primarily for high performance.

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• SciCrunch
• 13 years ago - by Anonymous

A group of scientists who collaborate and promote zebrafish neuroscience research. The consortium has opportunities for networking, scholarly publications and zebrafish-related symposia and conferences. The consortium is a supporter of the Zebrafish Neurophenome Project (ZNP), an initiative for a database of zebrafish behavioral and physiological data in an online, open source format.

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• SciCrunch
• 14 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Software for a Lab Information Management System (LIMS) for high-throughput screening of small molecule and RNAi biological assays.

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• SciCrunch
• 12 years ago - by Anonymous

Dataset of the spike and laser timestamps from Kravitz, Owen and Kretizer's 2012 paper "Optogenetic identification of striatal projection neuron subtypes during in vivo recordings." The code will analyze spike trains around laser pulses to determine if a cell is significantly activated by the laser, and therefore expresses an excitatory opsin, such as channelrhodopsin-2. It returns an excel sheet that simply identifies the activated cells.

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• SciCrunch
• 14 years ago - by Anonymous

Software for DNA Copy Number and loss of heterozygosity (LOH) analysis designed with high-throughput diagnostic laboratories in mind.

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• SciCrunch
• 12 years ago - by Anonymous

Platform-independent array copy number analysis software that provides straightforward yet comprehensive detection and reporting of copy number changes.

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• SciCrunch
• 12 years ago - by Anonymous

Software package for clonality testing providing statistical tests for clonality versus independence of tumors from the same patient based on their loss of heterozygosity (LOH) or genomewide copy number profiles.

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• SciCrunch
• 12 years ago - by Anonymous

A database of job listings

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• SciCrunch
• 15 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Software suite for the assembly and analysis of Sanger sequencing data within the SeqMan Pro application. The software's functions include: assembling reads into groups based on sequence names, trimming vector and poor quality data, restoration of sequence ends and designing of sequence primers.

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• SciCrunch
• 13 years ago - by Anonymous

Laboratory information management system for proteomics. The software works with 2DPAGE-based proteomics workflow.

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• SciCrunch
• 12 years ago - by Anonymous

Software R package for copy number variation analysis that allows analysis of the most common Affymetrix (250K-SNP6.0) array types and supports high-performance computing using snow and ff.

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• SciCrunch
• 12 years ago - by Anonymous

An open-source stand-alone computer program for visually comparing 2D gel images.

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• SciCrunch
• 12 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Software tool which interfaces OMSSA with Percolator, a post search machine learning method for rescoring database search results.

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• SciCrunch
• 12 years ago - by Anonymous

Software that automatically validates protein identifications made on the basis of peptides assigned to MS/MS spectra by database search programs such as SEQUEST.

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• SciCrunch
• 12 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. This website contains lecture videos from the events and discussions of the SEProt congress meeting, the theme of which is Human proteome. From Bench to Bedside. Sponsors: These videos are supported by the University of Navarra.

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• SciCrunch
• 16 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Computational Bioengineering Laboratory in the Division of Bioengineering at the National University of Singapore has expertise in mathematical modeling, software and algorithm development, numerical techniques such as finite element analysis, computer simulation and visualization, signal and image processing plus an understanding of the biological systems that drive our efforts. The following are the main themes underlying the Computational Bioengineering Laboratory projects: - Computational Biology - Computational Physiology - Biosignal & Bioimage Processing - Integrated Physiology & the Physiome Project

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• SciCrunch
• 16 years ago - by Anonymous

Software for analysis and DNA sequence assembly of Sanger data. It also provides visualizations and analysis of next-gen projects assembled by SeqMan NGen.

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• SciCrunch
• 13 years ago - by Anonymous

THIS RESOURCE HAS BEEN DISCONTINUED, documented April 15, 2016. New GEArray Expression Analysis Suite 2.0 was released at Dec 21, 2006, please read Release Notices for details. SABiosciences' GEArray Analysis Suite uses advanced Java functionality. In order to experience full functionality of this Portal, the following free programs and upgrades for PC and Macs should be properly installed. PC Environment Downloads Browser compatibility is not an issue on Windows systems, so all operating systems running Windows 98 and above and either Internet explorer or Netscape should be fine. Java 1.4.1 or above is required--this should download automatically upon the first entry into the Portal. If this does not happen, Java 1.5 is available for download from the following URL: Java 1.5 Mac Environment Downloads Browser compatibility is an issue, and Mac Operating Systems prior to Panther are not able to fully take advantage of this Portal's functionality. These programs need to be downloaded and installed in a specific order as follows: Panther 10.3.5 (Operating System), Safari 1.2 (Compatible Internet Browser) and Java 1.4.2 (Java environment). Abstract. INTRODUCTION: Toll-like receptors (TLR) comprehend an emerging family of receptors that recognize pathogen-associated molecular patterns and promote the activation of leukocytes. Surgical trauma and ischemia-reperfusion injury are likely to provide exposure to endogenous ligands for TLR in virtually all kidney transplant recipients. METHODS: Macroarray (GEArray OHS-018.2 Series-Superarray) analyses of 128 genes involved in TLR signaling pathway were performed in nephrectomy samples of patients with chronic allograft nephropathy (CAN) and acute rejection (AR, vascular and non vascular). The analysis of each membrane was performed by GEArray Expression Analysis Suite 2.0. RESULTS: Macroarray profile identified a gene expression signature that could discriminate CAN and AR. Three genes were significantly expressed between CAN and vascular AR: Pellino 2; IL 8 and UBE2V1. In relation to vascular and non-vascular AR, there were only two genes with statistical significance: IL-6 and IRAK-3. CONCLUSION: Vascular and non-vascular AR and CAN showed different expression of a few genes in TLR pathway. The analysis of nephrectomy showed that activation of TLR pathway is present in AR and CAN. Sponsor. This work was supported by the inconditional grant from Fundao de Amparo a Pesquisa do Estado de So Paulo (FAPESP, 04/08311-6), from Conselho Nacional de Pesquisa e Desenvolvimento (CNPq) and from Fundao Osvaldo Ramos.

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• SciCrunch
• 16 years ago - by Anonymous