Curator Dashboard

Web application as fully automated RNA structure modeling server. Used for RNA tertiary structure prediction.

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• RRID
• 11 months ago - by Anonymous

Core offers researchers and beekeepers, throughout the world, services to identify floral resources and evaluate characteristics of honey and pollen.

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• RRID
• 11 months ago - by Anonymous

Computational platform, which enables data-driven, fully-automated and ultra-fast cell-type identification based on given scRNA-seq data, combined with comprehensive cell marker database as background information. Deployed as both interactive web-tool and open-source R-package.

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• 11 months ago - by Anonymous

Software tool for selecting the best-fit model of evolution for DNA and protein alignments. Used for selection of DNA and Protein evolutionary models.

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• 11 months ago - by Anonymous

Core provides services including Sequencing, Library preparation, Bioinformatics Analysis and Processing. Experienced staff provide expertise to users.

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• SciCrunch
• 11 months ago - submitted by Edyta Vieth

Provides services in the conduct of exercise interventions, nutrition interventions, or prevention-based clinical interventions. Facility offers well-trained, specialized staff and inviting space for study participants to participate in population-based research.

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• 11 months ago - submitted by Cassie Sather

Software Python package to perform genomic selection. Predicts phenotypes from comprehensive multi-omics functional annotations with interpretable deep learning framework. Novel interpretable DL-based genomic prediction model that integrates comprehensive species- and tissue-level transcriptional regulatory functional annotations to predict phenotypes.

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• 11 months ago - submitted by ma wenlong

The python package 'DeepAnnotation' can be used to perform genomic selection (GS), which is a promising breeding strategy for agricultural breeding. DeepAnnotation predicts phenotypes from comprehensive multi-omics functional annotations with interpretable deep learning framework.

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• 11 months ago - submitted by ma wenlong

Open source Python-based image-analysis software that rapidly detects and segments berries and extracts morphometric data on fruit quality traits such as berry color, size, shape, and uniformity. Used for quantifying visual phenotypes of cranberries and other berries.

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• dkNET
• 11 months ago - by Anonymous

Software library and associated tools for reading and writing bigwig and bigbed files. High-performance BigWig and BigBed library in Rust.

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• RRID
• 11 months ago - by Anonymous

Software Python tool to perform motif enrichment analysis in sets of regions with different tools and identify high confidence TF cistromes.

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• RRID
• 11 months ago - by Anonymous

Backend application to process high-resolution histology images to DeepZoomImage format, made of smaller tiles, for use in the QUINT Workflow.

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• SciCrunch
• 11 months ago - by Anonymous

Software pipeline for universal mapping of ATAC-seq.

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• RRID
• 11 months ago - by Anonymous

Software Python package to optionally compute statistical test and add statistical annotations on plots generated with seaborn. Used to add statistical significance or custom annotations on seaborn plots.

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• RRID
• 11 months ago - by Anonymous

Software Python/Rust package for single-cell epigenomics analysis.

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• 11 months ago - by Anonymous

Software Python library to train, interpret, and apply deep learning models to DNA sequences. Comprehensive framework for DNA sequence modeling and design.

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• 11 months ago - by Anonymous

Software application for biological sequence analysis for the modern age.

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• RRID
• 11 months ago - by Anonymous

Software package to access the Borzoi models, which are convolutional neural networks trained to predict RNA-seq coverage at 32bp resolution given 524kb input sequences.

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• RRID
• 11 months ago - by Anonymous

Software Python module to simultaneously identify cell states and cis-regulatory topics from single cell epigenomics data.

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• RRID
• 11 months ago - by Anonymous

Software Python package for training sequence-based deep learning models on scATAC-seq data, for capturing enhancer code and for designing cell type-specific sequences.

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• 11 months ago - by Anonymous