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Facility is equipped with flow cytometers and cell sorters to examine cell samples within range of micron. Staff engage in experimentation, training, project collaboration, and consultation.
Biotechnology pilot plant capable of research and pilot scale production of microbial cells, recombinant proteins, and other microbial products over wide range of controlled conditions. Facility provides equipment and expertise to university affiliated and independent government and industry researchers interested in fermentation and related technologies, including cell separation and disruption, biomolecule production and purification, and process monitoring.
Automated Biological Calorimetry Facility provides infrastructure and support for individual investigators to undertake studies of macromolecule binding and folding, as well as protein and lipid quantification. Our calorimetry instruments are fully automated and require the least amount of sample of any commercially available instruments.Provides instrumentation and collaborative assistance for Isothermal titration calorimetry for studying ligand-macromolecule binding; Differential scanning calorimetry for investigating stability and folding thermodynamics. Staff is available to assist with project development and research.
Microscopy facility specializes in areas of optical microscopy, electron microscopy, and histology. Facility is equipped with confocal microscopes, research fluorescence microscopes, and transmission and scanning electron microscopes. Research staff engage in experimentation, training, project collaboration, and consultation.
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.
Our primary goal is to identify and quantify the small (
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
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.
Software tool for MOB typing for plasmid metagenomic fragments based on language model.
Software Matlab app for analysis of high density imaging data like that from Array Tomography.
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.
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.
Software for semi-automatic bone histomorphometry. Used for manual tracing of bone surfaces.
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.
Portal provides information on Cancer Statistics in Japan. Official website operated by National Cancer Center for cancer information.
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.
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.
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.
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.