Curator Dashboard

Cryo-Electron Microscopy Facility houses FEI Titan Krios microscope that offers data collection for life sciences while incorporating materials science applications. Used for creating super high definition 3D images of atoms and molecules. Facility allows for fully automated atomic resolution single particle and high contrast tomography tilt-series data collection. Additional microscopy components permit a full range of materials science applications, including EELS, STEM, and DPC. Facility also houses ThermoFisher Arctica G2.

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• SciCrunch
• 3 years ago - submitted by Craig Praul

Our primary goal is to identify and quantify the small (

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• SciCrunch
• 3 years ago - submitted by Craig Praul

he Genomics Core Facility provides services using several different next-generation sequencing platforms. Applications supported include: Whole-genome and transcriptome sequencing of non-model organisms Amplicon sequencing for metagenomic studies Differential expression analysis of mRNA and miRNA Degradome sequencing ChIP and RIP sequencing In addition, the facility continues to offer a variety of traditional services, including: Sanger DNA sequencing Genotyping of SNPs and VNTRs Real-time qPCR

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• SciCrunch
• 3 years ago - submitted by Craig Praul

Open source, adaptable tracking system for multiple rodents. Scalable and customizable system for tracking and behavior assessment consists of Raspberry Pi based video and RFID acquisition. Maximum of six rodents of any coat color can be tracked simultaneously in any user defined arena with few restrictions. For pose estimation and travel trajectory analysis, PyMouseTracks supports interfacing with open source packages such as DeepLabCut and Traja.

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• RRID
• 3 years ago - submitted by Samantha White

THIS TEST is a

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• NIF
• 3 years ago - by Anonymous

Software tool for MOB typing for plasmid metagenomic fragments based on language model.

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• RRID
• 3 years ago - submitted by Tao Feng

Software Matlab app for analysis of high density imaging data like that from Array Tomography.

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• RRID
• 3 years ago - submitted by Stephen Van Hooser

Platform is multi-analyte, multiplex spatial analysis technology that enables scientists to resolve complex biological challenges in areas such as oncology, neuroscience, and infectious disease. Platform produces contextual data sets that illuminate molecular interactions at subcellular resolution, while preserving the sample tissue.

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• RRID
• 3 years ago - by Anonymous

System for imaging of living and cleared specimens. Used to image large optically cleared specimens in toto with subcellular resolution. Dedicated optics, sample chambers and holders allow adaption to the refractive index of your chosen clearing method.

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• RRID
• 3 years ago - by Anonymous

Software for semi-automatic bone histomorphometry. Used for manual tracing of bone surfaces.

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• RRID
• 3 years ago - by Anonymous

Correlative electron microscopy and cross-platform imaging automation software. Imaging and correlative workflow software suite compatible with full line of Thermo Scientific SEM, DualBeam (FIB SEM) and TEM platforms.

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• RRID
• 3 years ago - by Anonymous

Portal provides information on Cancer Statistics in Japan. Official website operated by National Cancer Center for cancer information.

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• RRID
• 3 years ago - by Anonymous

Non-profit organisation dedicated to advancing disease, understanding and treatment through cutting-edge models. Provides mouse model resources for modelling human diseases. Provides research infrastructure for generation, phenotyping, archiving, and distribution of mouse models in Europe. Through collaboration with other infrastructures, it fosters global data sharing and contributes to tackling significant health challenges.

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• RRID
• 3 years ago - submitted by Montse Gustems

Software R toolbox for thorough metabolomic data analysis, integration and interpretation. Metabox 2.0 is updated version of R package Metabox and includes several methods for data processing, statistical analysis, biomarker analysis, integrative analysis and data interpretation.

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• RRID
• 3 years ago - submitted by Kwanjeera Wanichthanarak

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

Web application authoring interface that permits users to display, inspect, survey, and formulate knowledge statements to be added to SCKAN, as well as the ability to query and augment knowledge information within SCKAN, the SPARC Connectivity Knowledge Base of the Autonomic Nervous system.

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• RRID
• 3 years ago - submitted by Susan Tappan

Provides platform for visualizing multimodal single cell data across mammalian brain and aims to empower researchers to explore and analyze multiple whole brain datasets simultaneously. Allen Institute and its collaborators continue to add new modalities, species, and insights to the ABC Atlas. Atlas as part of Brain Knowledge Platform will enable neuroscience community to identify more cell types in brain; Investigate spatial location of cell types; Investigate gene expression and co-expression patterns in cell types; Refine boundaries and knowledge of brain regions defined by gene expression.

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• RRID
• 3 years ago - submitted by Anita Bandrowski

Software toolkit for Machine Learning Driven Data Analysis. Simplifies machine learning for data exploration, visualization and analysis.

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• RRID
• 3 years ago - submitted by Ali Hashemi Gheinani

Enhanced application on generating single cell gene expression profile for high resolution spatial transcriptomics. Registers spatial gene expression map and cell membrane/wall staining image with nuclei staining image as intermediary, thus cell membrane/wall outlines can be directly segmented from cell membrane/wall staining image without correcting nuclei boundaries.

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• RRID
• 3 years ago - submitted by Tongxuan Lv

Collection of statistical summaries for number of common cancer types. They were developed to provide quick overview of frequently requested cancer statistics. Available statistics may include incidence, mortality, survival, stage, prevalence, and lifetime risk. Links to additional resources from NCI including risk factors, treatment, and clinical trials are also provided. The statistics will be updated annually to coincide with the SEER data release.

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• RRID
• 3 years ago - submitted by Edyta Vieth