Curator Dashboard

Large scale, population-based, cross-sectional study containing interviews, physical exams, and biological samples. Data is prepared for analysis with SAS and SUDAAN, and is weighted in order to be representative of the New York population.

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• YaleTCC
• 10 years ago - submitted by Luis Marenco

Open source software toolkit for medical image conversion.

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• SciCrunch
• 3 years ago - submitted by Edyta Vieth

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 26, 2016. RiceCyc is a catalog of known and/or predicted biochemical pathways from rice (Oryza sativa). Pathways and genes presented in this catalog are primarily based on the annotations carried out by Gramene database project on the release 5 of the TIGR-assembly of Oryza sativa japonica cv. Nipponbare genome sequenced by IRGSP.

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• SciCrunch
• 14 years ago - by Anonymous

Portal for dataset discovery across a heterogeneous, distributed group of transcriptomics, genomics, proteomics and metabolomics data resources. These resources span eight repositories in three continents and six organisations, including both open and controlled access data resources.

• Resource
• SciCrunch
• 12 years ago - by Anonymous

Software tool to reconstruct phylogenetic trees from molecular sequence data by maximum likelihood. Allows analysis of large data sets and automatically assigns estimations of support to each internal branch. Computes pairwise maximum likelihood distances as well as branch lengths for user specified trees.Conducts statistical tests on the data set.

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• SciCrunch
• 3 years ago - submitted by Edyta Vieth

A probabilistic search tool for identifying damaged genes and their disease-causing variants in personal genome sequences. VAAST combines elements of phylogenetic conservation, amino acid substitution, and aggregative approaches to variant prioritization into a single unified likelihood-framework that allows users to accurately identify damaged genes and deleterious variants. The software can score both coding (SNV, indel and splice site) and non-coding variants (SNV), evaluating the cumulative impact of both types of variants simultaneously. It can identify rare variants causing rare genetic diseases and can also use both rare and common variants to identify genes responsible for common diseases.

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• SciCrunch
• 14 years ago - by Anonymous

Group whose goal is to improve health outcomes for individuals with X-linked adrenoleukodystrophy by raising disease awareness, improving education, providing support for and information to patients, and performing clinical ALD research.

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• dkNET
• 10 years ago - submitted by Ko-Wei Lin

US-based non-profit engaging bioimaging scientists across Canada, Mexico, the US and its territories by creating inclusive and supportive community to support bioimaging scientists through on-line events, registration assistance for professional development opportunities and the chance to visit peer imaging facilities to learn new techniques, develop or expand management skills, and/or image data management and analysis skills., through Exchange of Experience program.

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• RRID
• 3 years ago - by Anonymous

Experimental datasets of crystal structures and binding affinities for diverse protein-ligand complexes. Some datasets are generated in house while others are collected from the literature or deposited by academic labs, national centers, and the pharmaceutical industry. For the community to improve their approaches, they need exceptional datasets to train scoring functions and develop new docking algorithms. They aim to provide the highest quality data for a diverse collection of proteins and small molecule ligands. They need input from the community in developing target priorities. Ideal targets will have many high-quality crystal structures (apo and 10-20 bound to diverse ligands) and affinity data for 25 compounds that range in size, scaffold, and logP. It is best if the ligand set has several congeneric series that span a broad range of affinity, with low nanomolar to mid-micromolar being most desirable. They prefer Kd data over Ki data over IC50 data (no % activity data). They will determine solubility, pKa, logP/logD data for the ligands whenever possible. They have augmented some donated IC50 data by determining Kon/Koff and ITC data.

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• SciCrunch
• 14 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 9,2024. Core that provides services in Gene Editing Expertise Using CRISPR/CAS9, Conventional Transgenic Mouse Generation, Conventional Knockout, Knock-In Mouse Generation, and Cryopereservation of Sperm, Oocytes and Embryos.

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• SciCrunch
• 10 years ago - submitted by Kristen Jensen

Background Biomarker discovery exploiting feature importance of machine learning has risen recently in the microbiome landscape with its high predictive performance in several disease states. To have a concrete selection among a high number of features, Recursive Feature Elimination (RFE) has been widely used in the bioinformatics field. However, machine learning based RFE has factors that decrease the stability of feature selection. In this paper, we suggested methods to improve stability while sustaining performance. Results We exploited the abundance matrices of the gut microbiome (283 taxa at species level and 220 at genus level) to classify between patients with inflammatory bowel disease (IBD) and healthy control (1569 samples). We found that applying an already published data transformation before RFE improves feature stability significantly. Moreover, we performed an in-depth evaluation of different variants of the data transformation and identify those that demonstrate better improvement in stability while not sacrificing classification performance. To ensure a robust comparison, we evaluated stability using various similarity metrics, distances, the common number of features, and the ability to filter out noise features. We were able to confirm that the mapping by the Bray-Curtis similarity matrix before RFE consistently improves the stability while maintaining good performance. Multi-Layer Perceptron (MLP) algorithm exhibited the highest performance among eight different machine learning algorithms when a large number of features (a few hundred) were considered based on the best performance across 100 bootstrapped internal test sets. Conversely, when utilizing only a limited number of biomarkers as a tradeoff between optimal performance and method generalizability, the random forest algorithm demonstrated the best performance. Using the optimal pipeline we developed, we identified fourteen biomarkers for IBD at the species level and analyzed their roles using SHapley Additive exPlanations. Conclusion Taken together our work showed not only how to improve biomarker discovery in the metataxonomic field without sacrificing classification performance, but also provided useful insights for future comparative studies.

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• RRID
• 3 years ago - submitted by Marco Cappellato

A project producing datasets, software, and algorithms that is developing the technology to produce connectomes at the electron microscopic level of behaviorally-relevant neural circuits as well as the entire Drosophila nervous system. This technology will enable them to create a map of every neuron and synapse in the Drosophila nervous system, using novel approaches to electron microscopy (EM) as the foundation. In the same way that the fly genome paved the way for larger projects, including sequencing the human genome, Fly EM may ultimately contribute to our understanding of the human brain by establishing a fly "connectome" a map that shows how all neurons in the fly brain are connected to each other. They began their entry into EM reconstruction with the fly's adult visual system, where much is known about cell types from previous EM and histological studies, as well as ongoing studies in the Fly Light Project. In addition to establishing and publishing a fly connectome, Fly EM will make technology and methodology available that is needed to perform large-scale EM reconstructions. Fly EM will generally pursue an open policy with their datasets, software, and algorithms after relevant publications. When an EM reconstruction is published, the derived connectome and reconstructed neuronal skeletons will be made available online. The raw data and annotatations will be made available upon request as logistics dictate. To encourage further collaboration and scientific discovery, a small fraction of their raw data and corresponding segmentation will be made available independent of publication. Their goal is to enable others who wish to approach the many algorithmic challenges, but who do not have access to an EM facility, to have the data they need to support methods development, as well as their results to use as a benchmark. Fly EM emphasizes publication of supporting techniques and software approaches before major EM reconstruction releases to encourage rapid feedback from the community and adoption of their strategies. FlyEM maintains much of its software in the open-source repository GitHub:http://janelia-flyem.github.com. They will provide information on official release versions of these packages on git-hub when it reaches reasonable maturity.

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• SciCrunch
• 14 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 30,2025. Research core dedicated to translational research for diabetes with a focus on interventions for closing the gap in health disparities among various underserved populations. The core works to increase awareness of and techniques to survey populations equitably and effectively, evaluate the implementation of various interventions, and identify mediators for health disparities.

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• SciCrunch
• 10 years ago - submitted by Kristen Jensen

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• NIF
• 3 years ago - by Anonymous

Database of predicted transcription factors in completely sequenced genomes. The predicted transcription factors all contain assignments to sequence specific DNA-binding domain families. The predictions are based on domain assignments from the SUPERFAMILY and Pfam hidden Markov model libraries. Benchmarks of the transcription factor predictions show they are accurate and have wide coverage on a genomic scale. The DBD consists of predicted transcription factor repertoires for 930 completely sequenced genomes.

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• SciCrunch
• 17 years ago - by Anonymous

Core whose objective is to provide an infrastructure that facilitates the translation of basic research findings into the clinic. Its services include consultation, training, and education, biospecimen services, and facilitating data collection and analysis.

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• SciCrunch
• 10 years ago - submitted by Kristen Jensen

Software R package for genomic interval processing.Genomic regions processing using open-source command line tools to perform genome arithmetic e.g indexing, formatting and merging.

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• RRID
• 3 years ago - by Anonymous

Software repository that makes it easy for neuroscientists to find, use and share software tools. The Software Center is accessible to everyone: you can browse and download available software tools without registering. However, by creating an account, you will be able to post comments, and request to join development teams. The INCF Software Center and the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) are sharing content. Software tools hosted by NITRC also appear at the INCF Software Center. Your software tool will be available to all users of the Software Center. You will be able to upload documentation, executables and related files; track use of your software; create a wiki; and establish a development team. Registered Software Center users will be able to comment on and post reviews about your software, and can request to join your development team. INCF's vision of the Software Center is that it will become a communication enabler for software users as well as developers. Accordingly, future system features to be added include communication and collaboration functions. We also plan to include support services to allow software developers organize their software, track the use, and receive feedback for further improvement and development. Further development of the Software Center will be strongly driven by the user needs. Please let us know what features you would like to see added.

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• SciCrunch
• 14 years ago - by Anonymous

Core whose goals are to provide high throughput Clinical Biofluid Profiling Services (including initial web-based and in-person consultation, study design, sample preparation and processing, data acquisition, data analysis, protein purification, target identification, and specific assay development and validation) and services pertaining to Biomarker measurement and validation (including design of ELISA and Western Blots, measurement of known and emerging markers of acute and chronic kidney diseases, as well as consultation for biomarker statistics and clinical trials design).

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• SciCrunch
• 10 years ago - submitted by Kristen Jensen

MSKC is main gateway for Stanford faculty and students interested to study biological molecules using SLAC X-ray facilities and other major bioimaging facilities.

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• SciCrunch
• 4 years ago - submitted by Edyta Vieth