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http://folk.uio.no/thoree/FEST/

An R package for simulations and likelihood calculations of pair-wise family relationships using DNA marker data. (entry from Genetic Analysis Software)

Proper citation: R/FEST (RRID:SCR_013347) Copy   

•   Source: SciCrunch Registry

http://www-sequence.stanford.edu/group/candida/

The Stanford Genome Technology Center began a whole genome shotgun sequencing of strain SC5314 of Candida albicans. After reaching its original goal of 1.5X mean coverage of the haploid genome (16Mb) in summer, 1998, Stanford was awarded a supplemental grant to continue sequencing up to a coverage of 10X, performing as much assembly of the sequence as possible, using recognizable genes as nucleation points. Candida albicans is one of the most commonly encountered human pathogens, causing a wide variety of infections ranging from mucosal infections in generally healthy persons to life-threatening systemic infections in individuals with impaired immunity. Oral and esophogeal Candida infections are frequently seen in AIDS patients. Few classes of drugs are effective against these fungal infections, and all of them have limitations with regard to efficacy and side-effects.

Proper citation: Sequencing of Candida Albicans (RRID:SCR_013437) Copy   

•   Source: SciCrunch Registry

http://www.physci.ucla.edu/research/GomezPinilla/

We are interested on the mechanisms by which environmental factors affect neuronal health. We have found that trophic factors endogenous to the brain and spinal cord can be induced by the practice of select behaviors. We have recently reported that physical activity, learning, and nutritional factors control neurotrophins in the brain. These findings opened the exciting possibility that regulation of trophic factors by behavior can be a pivotal mechanism by which specific experiences can impact the structure and function of the CNS. It may account for the improvement of CNS function after trauma provided by rehabilitative therapies. On the contrary, it may explain the decay in function in aging or degenerative diseases following a lack of stimulation. These two avenues provide direction for my research program: 1) How trophic factors induced by activity can help functional recovery following brain and spinal cord trauma. We are using several exercise models to boost the production of trophic factors in the brain and spinal cord. Our goal is to provide critical information to guide the design of behavioral therapies for the reduction of the severity of insult or disease, and to increase CNS function. 2) We are evaluating the effects of lifestyle on trophic factor production, with resulting effects on circuit remodeling, synaptic function, and cognition. We believe that changes in trophic factor as a result of select experiences can affect neuronal health with profound consequences for cognitive function. :lab :

Proper citation: Neurotrophic Lab (RRID:SCR_013572) Copy   

•   Source: SciCrunch Registry

http://orwh.od.nih.gov/cfs.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. This website endeavors to provide information on the Chronic Fatigue Syndrome Working Group (CFSWG) and its programs that is helpful to researchers, health care providers, people with CFS and their families, and the general public. :The mission of the Trans-NIH Working Group for Research on Chronic Fatigue Syndrome is to: :* Stimulate and support research on CFS within the context of the missions of all Institutes, Centers and Offices. :* Collaborate and coordinate the research agendas of all Institutes, Centers and Offices to issue on a regular basis joint Program Announcements or theme related Request for Applications to further interdisciplinary research in CFS. :* Present new knowledge to and facilitate novel theoretical approaches to CFS among NIH scientists. :* Plan and sponsor scientific symposia to foster awareness, provoke new scientific interest, and generate interdisciplinary collaboration on CFS among both the NIH and Academic medical community.

Proper citation: Chronic Fatigue Syndrome (RRID:SCR_013641) Copy   

•   Source: SciCrunch Registry

http://biomaterials.syr.edu/

Welcome to the Syracuse Biomaterials Institute! We are a new, interdisciplinary institute focused on research in biomaterials, smart medical devices, and biological/tissue-engineered constructs. Biomaterials are natural and synthetic substances designed to treat, augment, or replace tissues and organs of the human body as treatments to disease or injury. An outgrowth of the long-standing Biomaterials Group in the Biomedical and Chemical Engineering Department, the Syracuse Biomaterials Institute (SBI) was launched in Fall, 2007, through strategic investments by Syracuse University, New York State Foundation for Science, Technology and Innovation (NYSTAR), and private donations. SBI is a cohesive collection of highly collaborative faculty spanning eight (8) academic units, including faculty from SUNY Upstate Medical University and SUNY College of Environmental Science and Forestry. Our researchers are engaged in a wide spectrum of problems, ranging from fundamental studies of the biochemical and physical processes controlling cell functions to the development of new technologies for biomedical applications. In addition to our collaborative research and teaching activities, we are excited to be designing our future SBI home, planned for Fall 2009, that will collocate our research groups and central laboratory facilities. :jobs board, postdoctoral training program, graduate training program, portal :

Proper citation: Syracuse Biomaterials Institute (RRID:SCR_013626) Copy   

•   Source: SciCrunch Registry

https://github.com/mrc-ide/PhyDyn

Sofware package for performing Bayesian phylogenetic inference under models that deal with structured populations with complex population dynamics. Enables simultaneous estimation of epidemiological parameters and pathogen phylogenies. Epidemiological modelling in BEAST.

Proper citation: PhyDyn (RRID:SCR_018544) Copy   

•   Source: SciCrunch Registry

https://github.com/stekhoven/missForest

Software R package to impute missing values particularly in case of mixed type data. Non parametric, mixed type imputation method for any type of data for statistical software R. Predicts missing values.

Proper citation: missForest (RRID:SCR_018543) Copy   

•   Source: SciCrunch Registry

https://aspredicted.org

Website for study pre-registration. Defines minimum required criteria for pre-registration and allows authors to pre-register their study. It is standardized pre-registration that requires only what is necessary to separate exploratory from confirmatory analyses.

Proper citation: AsPredicted (RRID:SCR_018789) Copy   

•   Source: SciCrunch Registry

https://opencor.ws/

Open source cross platform modeling environment for reproducible science. Used to organise, edit, simulate and analyse models described in CellML format, using SED-ML and COMBINE archives.

Proper citation: OpenCOR (RRID:SCR_019001) Copy   

•   Source: SciCrunch Registry

http://amphibian.hiroshima-u.ac.jp/english/ARC_HP_English_ver./english_page.html

Stock center that provides amphibian organisms, frogs and newts, primarily to Japanese investigators. The center runs the National BioResource Project (NBRP) Clawed frogs / Newts, which is financially supported by the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan, to distribute these resources. Contributes to maintenance of biologically important strains of frogs and study biological characteristics of amphibian focusing genetics, developmental regulation, speciation, phylogeny, phenotype expression, and environment-induced mutagenesis.

Proper citation: Hiroshima University Amphibian Research Center (RRID:SCR_019015) Copy   

•   Source: SciCrunch Registry

http://www.softberry.com/berry.phtml?topic=fgenesh_plus_plus&group=help&subgroup=pipelines

Software tool as pipeline for automatic prediction of genes in eukaryotic genomes based on Softberry gene finding software.

Proper citation: Fgenesh plus plus (RRID:SCR_018928) Copy   

•   Source: SciCrunch Registry

https://nemar.org

Portal for human electrophysiological data, supports, sharing and in depth analysis of identified human neuroelectromagnetic brain data including scalp EEG, its magnetic counterpart, MEG, and, intracranial iEEG and ECoG. Open access EEG and MEG data archives, analysis, and visualization. Neuroelectromagnetic data, tools, and compute resource.

Proper citation: NEMAR (RRID:SCR_019100) Copy   

•   Source: SciCrunch Registry

https://docs.osparc.io

Simulation platform that enables users to create, access, tune, and run models or computational algorithms through web based interface. Web interactive simulation platform that hosts SPARC computational models and solvers. Allows collaborative development and sharing, model coupling and cloud based execution, data visualization and analysis, and ensures sustainability of computational models developed within SPARC. Enables users to create predictive, multiscale, multi-physics models spanning from modulation sources acting on peripheral nervous system (PNS) to resulting modulation of organ functional response.

Proper citation: o²S²PARC (RRID:SCR_018997) Copy   

•   Source: SciCrunch Registry

https://usdrn.org/

Portal for research on urinary stones in adults and children in order to learn more about who forms kidney stones, treatments and prevention. Network comprises of experts including adult and pediatric urologists, adult and pediatric nephrologists, pediatricians, emergency department physicians, clinical trialists, nutritionists, behavioral scientists, and radiologists. Duke Clinical Research Institute is Scientific Data Research Center and with clinical sites including University of Pennsylvania Children Hospital of Philadelfia, University of Texas Southwestern Medical Center, University of Washington, Washington University in St. Louis, work together in planning, executing, and analyzing results from USDRN studies.

Proper citation: Urinary Stone Disease Research Network (RRID:SCR_019059) Copy   

•   Source: SciCrunch Registry

https://thesugarscience.org

Interactive digital platform helping scientists who study type 1 diabetes connect, collaborate, and gain funding for their best ideas. All volunteer team has received much positive support from the global population of scientists studying type 1 diabetes, as well as from Beyond Type 1, JDRF, and IPITA. Provides curated conversations, events and technology to scientific T1D focused audience. Non profit entity funded by donations and sponsorships with industry and academic partners to provide unique collaborative benefits and programs to researchers in the T1D academic research community.

Proper citation: thesugarscience (RRID:SCR_020250) Copy   

•   Source: SciCrunch Registry

https://www.nurseshealthstudy.org/

Portal about prospective investigations into risk factors for major chronic diseases in women. Nurses were selected as study population because of their knowledge about health and their ability to provide complete and accurate information regarding various diseases, due to their nursing education.The largest longitudinal study of women. Started in 1976, involving 275000 participants.

Proper citation: Nurses Health Study (RRID:SCR_019144) Copy   

•   Source: SciCrunch Registry

https://github.com/mlinderm/npsv

Software Python tool for standalone genotyping of deletion and insertion structural variants in short read whole genome sequencing data. Implements machine learning based approach for SV genotyping that employs NGS simulation to model the combined effects of the genomic region, sequencer and alignment pipeline.

Proper citation: NPSV (RRID:SCR_020984) Copy   

•   Source: SciCrunch Registry

https://www.scionics.com/pyrat_de.html

Software tool for management of animal facility data by Scionics Computer Innovation GmbH. Used by laboratory animal facilities. Used by researchers, animal house managers, animal keepers and others to access their data from same source. Available in English, French, German, Italian, Portuguese and Spanish.

Proper citation: Python based Relational Animal Tracking (RRID:SCR_021014) Copy   

•   Source: SciCrunch Registry

https://github.com/dmnfarrell/epitopepredict

Open source software tool as programmatic framework and command line tool designed to aid process of MHC binding prediction. Provides access to multiple binding prediction algorithms under single interface and scales for whole genomes using multiple target MHC alleles.Software should be run on Linux operating system. Ubuntu is recommended but most major distributions will be fine. Windows is not supported.

Proper citation: epitopepredict (RRID:SCR_019221) Copy   

•   Source: SciCrunch Registry

https://github.com/bgcarlisle/Numbat

Software tool for managing extraction of large volumes of data from primary sources among multiple users, and then reconciling differences between them. Designed for use in systematic review projects in academic context.

Proper citation: Numbat (RRID:SCR_019207) Copy   

•   Source: SciCrunch Registry