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Private Methodist affiliated university with its main campus in Stockton, California, and graduate campuses in San Francisco and Sacramento.

• Organization
• SciCrunch
• 13 years ago - submitted by Eddy Kim

French public university.

• Organization
• SciCrunch
• 16 years ago - submitted by Andrea Stagg

The Statistics and Bioinformatics research group has as its main objectives the development of methods and tools to deal with problems appearing in the interface between Statistics and Bioinformatics. We started focusing in DNA microarrays but we are also interested in statistical methods for ''omics'' data integration and next generation sequencing (NGS). Our group collaborates with different research groups in the fields of biology and biomedicine, to whom it offers statistical support for problems which are specifically statistic in nature, such as experimental design or microarray data analysis, and also in more general aspects, such as modeling, analysis or data mining. After a first period of collaboration agreements with the Fundaci�� Vall d''Hebr��n Institut de Recerca we contributed to the creation of the Statistics and Bioinformatics Unit (UEB) which provides statistical and bioinformatical support to VHIR researchers.

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• SciCrunch
• 15 years ago - by Anonymous

Foundation scientists and physicians conduct breakthrough research to improve care for children as well as train the next generation of investigators. Cincinnati Children's Research Foundation is dedicated to advancing basic, translational, clinical and outcomes-based research. Why choose our cores for your research? We can provide you with cutting-edge, cost-effective technology and data analysis that would be unattainable on an individual research basis. Our fee-for-service program also offers unique studies that you can't find anywhere else. Our faculty also has access to the research cores hosted at the University of Cincinnati College of Medicine. * Animal Behavioral Core * Cardiovascular Imaging Core * Cell Manipulations Laboratory * Cell Processing Core * Cincinnati Biobank * Cincinnati Center for Nutritional Research and Analysis * Comprehensive Mouse and Cancer Core * Gene Expression Microarray Core * Genetic Variation and Gene Discovery Core * Imaging Research Center * Laser Capture Microdissection Microscopy * Lenti-shRNA Library Core * Pathology Research Core * Pluripotent Stem Cell Facility * Research Flow Cytometry Core * Stem Cell Processing Core Lab * Transgenic and Gene Targeting Core * Translational Core Labs * Translational Trials Development and Support Laboratory (TTDSL) * Vector Production Facility * Veterinary Services * Viral Vector Core Support Services: We provide expert consultation, including grant proposal design, data management and regulatory compliance, to investigators at Cincinnati Children's. Research Education and Training: The Cincinnati Children's Research Foundation offers research-based education and training options for scientists, often in conjunction with the University of Cincinnati. High School Programs, Undergraduate Programs, Graduate Degree Programs, Medical Student Program, Postgraduate Programs, Postdoctoral Programs

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• SciCrunch
• 15 years ago - by Anonymous

Software for identifying differentially methylated regions between unique samples using array based methylation profiles. It allows researchers to compare n greater than or equal to 2 unique samples with regard to their methylation profile. The (pairwise) comparison of n unique single samples distinguishesit from other existing pipelines as these often compare groups of samples in either single CpG locus or region based analysis. DMRforPairs defines regions of interest as genomic ranges with sufficient probes located in close proximity to each other. Probes in one region are optionally annotated to the same functional class(es). Differential methylation is evaluated by comparing the methylation values within each region between individual samples and (if the difference is sufficiently large), testing this difference formally for statistical significance.

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• SciCrunch
• 12 years ago - by Anonymous

The Biostatistics Core provides statistical support for cancer-related research at UCSF, focusing particulary on applications in clinical trials and population studies. The Computational Biology Core supports applications to genomics, genetics and molecular biology. Core faculty have expertise in study design, protocol and proposal development and review, data analysis, and publication of results. Support for Cancer Center investigators participating in established Site Committees is typically handled by the faculty member assigned to that committee. Other requests can be directed to the consulting service request page maintained by the UCSF Clinical & Translational Science Institute (CTSI). These requests will then be assigned to a Core faculty member. Basic consulting services are generally provided free of charge to Cancer Center Members. Members requiring frequent assistance are encouraged to provide regular salary support to a Core statistician when possible to support more extensive requests and for long-term projects. Services: * Study Design * Guidance on Study Conduct * Data Analysis and Reporting of Study Results * Teaching resources

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• SciCrunch
• 15 years ago - by Anonymous

The research of the group concentrates on the molecular biology of Gram-positive bacteria, with Bacillus subtilis and Lactococcus lactis as the main model organisms. A number of important (human) pathogens are also investigated: Bacillus cereus, Streptococcus pneumoniae and Enterococcus faecalis. The nature of the research is both fundamental and application-oriented. Transcript- and protein profiling by high-throughput technologies such as DNA microarrays and proteomics tools are being used. The very large data sets generated are analyzed by employing existing and novel bioinformatics tools. Major lines of research are in the field of functional genomics of these organisms, using systems- and synthetic biology approaches.

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• SciCrunch
• 15 years ago - by Anonymous

Scientists at the Yates Lab at The Scripps Research Institute (TSRI) rely on information yielded by tandem mass spectrometry to identify proteins from complex mixtures. Using this powerful technique, researchers draw upon a cross section of fields to increase the scope, sensitivity, and throughput of technologies for practical proteomics. Biologists provide the questions that drive our research. By identifying complexes that are poorly understood or organism-wide issues requiring further exploration, we gain a theoretical understanding of issues that are tractable only through proteomic strategies. Analytical chemists and biochemists improve our tools for revealing the proteins present in biological samples. Targets for optimization include the isolations used to obtain proteins, the steps to generate peptides from these proteins, and the separation of peptides en route to the mass spectrometer. Chemistry is vital to increasing power of proteomic technology. Computer science yields tools on two scales. First, the sequence corresponding to each peptide''s tandem mass spectrum must be identified. Once those identifications have been completed, additional tools are needed to summarize and organize these identifications.

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• SciCrunch
• 14 years ago - by Anonymous

Mark Musen''s laboratory studies components for building knowledge-based systems, controlled terminologies and ontologies, and technology for the Semantic Web. For more than two decades, Musen''s group has worked to elucidate reusable building blocks of intelligent systems, and to develop scalable computational architectures for systems with significant applications in biomedicine. Informatics is the study of information: its structure, its communication, and its use. As society becomes increasingly information intensive, the need to understand, create, and apply new methods for modeling, managing, and acquiring information has never been greater especially in biomedicine. BMIR is home to world class scientists and trainees developing cutting-edge ways to acquire, represent, process, and manage knowledge and data related to health, health care, and the biomedical sciences. Our faculty, students, and staff are committed to ensuring the biomedical community is properly equipped for the information age, and believe our efforts will provide the structure for the burgeoning revolution of health care and the biomedical sciences.

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• SciCrunch
• 15 years ago - by Anonymous

NYU Bioinformatics group applies algorithmic, statistical, and mathematical techniques to solve problems of interest to biology, biotechnology and biomedicine. The group focuses on bioinformatics, computational biology and systems biology with many active projects in areas ranging from single molecules to entire populations: Analysis of Single-Molecule/Single-Cell Data, SPM-based Transcriptomic Profiling, Whole-Genome Haplotype Sequencing using SMASH (Single Molecule Approaches to Haplotype Sequencing), SUTTA (Scoring and Unfolding Trimmed Tree Assembler) assembly algorithm, Analysis of Spatio-Temporal Data, Model Checking and Model Building for Systems Biology, GOALIE-based Phenomenological Models and their Verification, Causality Analysis, Causal Models and their Verification, Analysis of EHR (Electronic Health Record Data) and Disease Models (e.g., Chronic Fatigue Syndrome, Congestive Heart Failure, Deep Vein Thrombosis, etc.), Models of Cancer, Applications to Pancreatic Cancer, Polymorphisms and Biomarkers, Strategies for Group Testing, Epidemiological and Bio-Warfare Models, Planning with Large Agent Networks against Catastrophes (PLAN C), Population Genomics, and Genome Wide Association Studies (GWAS). The group has received its funding from Air Force, Army, CCPR, DARPA, NIH, NIST, NSF, NYSTAR, etc. and various other governmental and commercial entities. Currently, the group is part of an NSF funded Expedition in Computing project (CMACS: Center for Modeling and Analysis of Complex Systems at CMU) and collaborates widely, both nationally and internationally. The group is highly multi-disciplinary, attracting researchers and students from mathematics, statistics, computer science, and biology who team up with physicians, physicists, and chemists as well as professionals in their own disciplines. This group is led by Prof. Bud Mishra, a professor of computer science and mathematics at NYU''s Courant Institute of Mathematical Sciences.

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• SciCrunch
• 15 years ago - by Anonymous

The research in the lab focuses on computational modeling of biological macromolecules and their assemblages and predicting biophysical quantities associated with them. The main focus of the lab is the development and maintenance of the popular software package DelPhi, which calculates electrostatic potential and energies of systems comprised of biological macromolecules. In addition, we are interested in modeling disease-causing missense mutations, pKa''s of amino acids and nucleic groups and pH-dependence of stability and binding. In parallel with in silico modeling, the lab actively collaborates with experimetalists to better understand molecular mechanisms of biological reactions and interactions. The combination of the methods of Computational Biophysics and Bioinformatics with experimental results is an essential approach utilized in our research.

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• SciCrunch
• 15 years ago - by Anonymous

A dataset of an on-going multi-level longitudinal survey in Indonesia that collects extensive information on socio-economic and demographic characteristics of respondents, as well as extremely comprehensive interviews with local leaders about community services and facilities. The survey is ideally suited for research on topics related to important dynamic aging processes such as the transition from self-sufficiency to dependency, the decline from robust health to frailty, labor force and earning dynamics, wealth accumulation and decumulation, living arrangements and intergenerational transfers. The first wave of IFLS was fielded in 1993 and collected information on over 30,000 individuals living in 7,200 households. The sample covers 321 communities in 13 provinces in Indonesia and is representative of about 83% of the population. These households were revisited in 1997 (IFLS2), 2000 (IFLS3), and 2007-8 (IFLS4). A 25% sub-sample of households was re-interviewed in 1998 (IFLS2+). Special attention is paid to the measurement of health, including the measurement of anthropometry, blood pressure, lung capacity, a mobility test and collection of dry blood spots by a nurse or doctor. In addition to comprehensive life history data on education, work, migration, marriage and child bearing, the survey collects very detailed information on economic status of individuals and households. Links with non co-resident family members are spelled out in conjunction with information on borrowing and transfers. Information is gathered on participation in community activities and in public assistance programs. Measurement of health is a major focus of the survey. In addition to detailed information about use of private and public health services along with insurance status, respondents provide a self-reported assessment of health status. Detailed information on the local economy and prices of goods and services are also collected. These data may be matched with the individual and household-level data. Considerable attention has been placed on minimizing attrition in IFLS. In each re-survey, about 95% of households have been re-contacted. Around 10-15% of respondents have moved from the location in which they were interviewed in the previous wave. In addition, individuals who split-off from the original households have been followed. They have added around 1,000 households to the sample in 1997 and about 3,000 households in 2000. Data Availability: IFLS1 data are available through ICPSR as study number 6706. Data from subsequent waves of the IFLS can be accessed from the RAND project Website. * Dates of Study: 1993-2008 * Study Features: Longitudinal, International, Anthropometric Measures, Biomarkers * Sample Size: ** 1993: 22,000 (IFLS1) ** 1997: 33,000 (IFLS2) ** 1998: 10,000 (IFLS2+) ** 2000: 37,000 (IFLS3) ** 2008: 44,103 (IFLS4) Links: * IFLS1 ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06706 * IFLS ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00184

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• SciCrunch
• 14 years ago - by Anonymous

Virtual Biology Lab portal from the University of Nice Sophia Antipolis; Nice; France. Offered are a variety of software including: * GenBank2Treedyn: Extract annotations from GenBank files for: ** More convenient alignments and phylogeny (replace def line of fasta file by GI number) ** Extremely powerful annotations of phylogenetic trees with TreeDyn. * THEA: Analyses of DNA chip data with ontologies * Blast2Tree: Blast server for the identification of procaryotes * Dashboard: e-Tool for data exchanges among partners, DNA chips design and developement * Oligo Heat Map: Check thermodynamical parameters for PCR primers and compute graphical representation to show specificity of target sequences * EmblEx: A cgi tool to parse and extract data from EMBL entries to various formats * Miscellaneous software ** Jane plugin: Add a small panel to Jane server to retrieve PMID of publications ** EtBlast plugin: Add a small panel to EtBlast server to retrieve PMID of publications ** Oligo Builder: Get the oligomers from a set of target sequences by avoiding non-target sequences

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• SciCrunch
• 15 years ago - by Anonymous

A pipeline for analyzing whole genome bisulfite sequencing (WGBS) data.

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• SciCrunch
• 13 years ago - by Anonymous

Biomedicine can only be understood in the context of genomics and with the concourse of bioinformatics. Our department aims to tackle biomedical problems from a system's biology perspective. Following this, the general objective we seek through the main lines of research is to relate the mutations (Pharmacogenomics and Comparative Genomics) to their effect at cellular and phenotypic level (Functional Genomics) trying to understand the mechanism of action (Structural Genomics). Systems Biology Genes operate within an intricate network of interactions that we have only recently started to envisage. Many higher-order levels of interaction are continuously being discovered. In this scenario we are interested in developing methods and tools which can help to understand large-scale experiments from a systems biology perspective. Comparative genomics We are interested in the analysis of patterns and processes occurred during the evolution of our genome, and in the application of the evolutionary thought in human health and disease. * Adaptive Human Evolution * Evolutionary Pharmacogenetics * SNP's and Human Disease Structural genomics Our Unit aims to develop and apply computational methods for understanding the molecular mechanisms of cell regulation beyond proteins. In particular, we apply our methods to study the interaction of small chemical compounds with proteins and to characterize their molecular actions. We are also developing methods for RNA 3D structure prediction with the aim of applying them to understand the effects of non-coding RNA molecules. Finally, in collaboration with experimentalists, we are working in determining the first ever 3D structure of a genomic domain in human.

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• SciCrunch
• 15 years ago - by Anonymous

The Pr��ncipe Felipe Research Centre (CIPF), which was inaugurated by their Royal Highnesses the Prince and Princess of Asturias on 17th March 2005, is a centre dedicated to biomedical research, with the aim of taking on new challenges in the field of basic research and encouraging scientific works of excellence. The construction of the Centre was carried out thanks to the Regional Development Funds from the European Union, and from the Regional Government (Generalitat Valenciana) through its Ministry of Health. The current financing of the CIPF comes mainly from the investment made by the Generalitat Valenciana through the Ministry of Health, as well as the Regenerative Medicine Programme, the fruit of an agreement between the Institute of Health Carlos III and the Ministry of Health for basic and translation research in this field. The CIPF takes the research tradition from the then Valencian Cytological Research Institute and the Valencian Biomedical Research Foundation, with the aim of consolidating and expanding this research. Therefore the activity in the CIPF can be divided into three main strategic work areas: The Regenerative Medicine area focuses its research on cellular therapy and interdisciplinary research in human embryonic and adult stem cells, with the aim of regenerating damaged organs to improve human health. The Chemical and Quantative Biology area aims to understand, through the application of (bio) chemical, genetic, and bioinformatic methods, to understand the molecular mechanisms that control the biological processes and alterations that lead to pathological conditions. The Biomedicine area focuses on understanding the molecular bases of human pathologies that require new diagnostic and clinical procedures for their identification and treatment, pathologies such as cancer, neurological pathologies and rare illnesses.

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• SciCrunch
• 15 years ago - by Anonymous

The Bioinformatics, Algorithmics, and Data Mining group BIIT lead by prof. Jaak Vilo is a joint research group between the Department of Computer Science (University of Tartu), Quretec, and the Estonian Biocenter. Our main research topics and capabilities include the gene regulation, gene expression data analysis, biological data mining, systems biology, combinatorial pattern matching, developing software for biomedical research databases, as well as partnering in stem cell and cancer related projects. Software * MEM - Multi-Experiment-Matrix -- large-scale gene expression data queries and mining (Genome Biology 2009) * g:Profiler family of tools for functional assessment of gene groups, gene ID mappings, orthology and expression similarity searches. (NAR web server issue 2007) * KEGGanim - visualisation of high-throughput data on biological pathway charts (Bioinformatics, 2007) * GraphWeb - a tool for mining large biological networks (NAR Web server issue 2008) * FunGenES data atlas * More software tools

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• SciCrunch
• 15 years ago - by Anonymous

Wandora is a general purpose information extraction, management and publishing application based on Topic Maps and Java. Wandora has graphical user interface, layered and merging information model, multiple visualization models, huge collection of information extraction, import and export options, embedded HTTP server with several output modules and open plug-in architecture. Wandora is a FOSS application with GNU GPL license. Wandora is well suited for constructing ontologies and information mashups. Wandora is capable of extracting and converting a wide range of open data feeds to topic map formats. Beyond topic map conversion, this feature allows Wandora user to aggregate multidimensional information mashups where information from Flickr interleaves with information from GeoNames and YouTube, for example. Wandora is a software application to build, edit, publish and visualize information graphs, especially topic maps. Wandora is written in Java and suits for * Collecting, combining, aggregating, managing, refining and publishing information and knowledge graphs * Designing information, information modeling and prototyping * Information mashups * Ontology creation and management * Mind and concept mapping * Language technology applications * Graph visualizations * Knowledge format conversions * Digital preservation * Data journalism * Open data projects * Linked data projects Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

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• SciCrunch
• 15 years ago - by Anonymous

Repository of phylogenetic information, specifically user-submitted phylogenetic trees and the data used to generate them. TreeBASE accepts all kinds of phylogenetic data (e.g., trees of species, trees of populations, trees of genes) representing all biotic taxa. Data in TreeBASE are exposed to the public if they are used in a publication that is in press or published in a peer-reviewed scientific journal, book, conference proceedings, or thesis. Data used in publications that are in preparation or in review can be submitted to TreeBASE but will not be available to the public until they have passed peer review.

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• SciCrunch
• 17 years ago - by Anonymous

TAIR Keyword Browser searches and browses for Gene Ontology, TAIR Anatomy, and TAIR Developmental stage terms, and allows you to view term details and relationships among terms. It includes links to genes, publications, microarray experiments and annotations associated with the term or any children terms. Platform: Online tool

• Resource
• SciCrunch
• 15 years ago - by Anonymous