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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
http://easybioai.com/sc2disease/
Manually curated database of single cell transcriptome for human diseases. scRNA-seq database derived from numerous human studies. Provides researchers with encyclopedia of biomarkers at level of genes, cells, and diseases.
Proper citation: SC2diseases (RRID:SCR_019093) Copy
http://www.megabionet.org/atpid/webfile/
Centralized platform to depict and integrate the information pertaining to protein-protein interaction networks, domain architecture, ortholog information and GO annotation in the Arabidopsis thaliana proteome. The Protein-protein interaction pairs are predicted by integrating several methods with the Naive Baysian Classifier. All other related information curated is manually extracted from published literature and other resources from some expert biologists. You are welcomed to upload your PPI or subcellular localization information or report data errors. Arabidopsis proteins is annotated with information (e.g. functional annotation, subcellular localization, tissue-specific expression, phosphorylation information, SNP phenotype and mutant phenotype, etc.) and interaction qualifications (e.g. transcriptional regulation, complex assembly, functional collaboration, etc.) via further literature text mining and integration of other resources. Meanwhile, the related information is vividly displayed to users through a comprehensive and newly developed display and analytical tools. The system allows the construction of tissue-specific interaction networks with display of canonical pathways.
Proper citation: Arabidopsis thaliana Protein Interactome Database (RRID:SCR_001896) Copy
http://fcon_1000.projects.nitrc.org/indi/CoRR/html/
Consortium that has aggregated resting state fMRI (R-fMRI) and diffusion imaging data from laboratories around the world, creating an open science resource for the imaging community, that facilitates the assessment of test-retest reliability and reproducibility for functional and structural connectomics. Given that this was a retrospective data collection, they have focused on basic phenotypic measures that are relatively standard in the neuroimaging field, as well as fundamental for analyses and sample characterization. Their phenotypic key is organized to reflect three classifications of variables: 1) core (i.e., minimal variables required to characterize any dataset), 2) preferred (i.e., variables that were strongly suggested for inclusion due to their relative import and/or likelihood of being collected by most sites), and 3) optional (variables that are data-set specific or only shared by a few sites). CoRR includes 33 datasets consisting of: * 1629 Subjects * 3357 Anatomical Scans * 5093 Resting Functional Scans * 1302 Diffusion Scans * 300 CBF and ASL Scans
Proper citation: Consortium for Reliability and Reproducibility (RRID:SCR_003774) Copy
http://hapmap.ncbi.nlm.nih.gov/
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A multi-country collaboration among scientists and funding agencies to develop a public resource where genetic similarities and differences in human beings are identified and catalogued. Using this information, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. All of the information generated by the Project will be released into the public domain. Their goal is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. HapMap project related data, software, and documentation include: bulk data on genotypes, frequencies, LD data, phasing data, allocated SNPs, recombination rates and hotspots, SNP assays, Perlegen amplicons, raw data, inferred genotypes, and mitochondrial and chrY haplogroups; Generic Genome Browser software; protocols and information on assay design, genotyping and other protocols used in the project; and documentation of samples/individuals and the XML format used in the project.
Proper citation: International HapMap Project (RRID:SCR_002846) Copy
http://www.nitrc.org/projects/gig-ica/
Software toolbox for group-information guided Independent Component Analysis (ICA). In GIG-ICA, group information captured by standard Independent Component Analysis (ICA) on the group level is used as guidance to compute individual subject specific Independent Components (ICs) using a multi-objective optimization strategy. For computing subject specific ICs, GIG-ICA is applicable to subjects that are involved or not involved in the computation of the group information. Besides the group ICs, group information captured from other imaging modalities and meta analysis could be used as the guidance in GIG-ICA too.
Proper citation: Group Information Guided ICA (RRID:SCR_009491) Copy
https://academic.oup.com/bioinformatics/article/34/7/1229/4657077
Software R/Shiny application for interactive creation of Circos plot. Used for creation of Circos plot interactively.
Proper citation: shinyCircoss (RRID:SCR_022367) Copy
https://www.nitrc.org/projects/rshrf
Software toolbox for resting state HRF estimation and deconvolution analysis. Matlab and Python toolbox that implements HRF estimation and deconvolution from resting state BOLD signal. Used to retrieve optimal lag between events and HRF onset, as well as HRF shape. Once that HRF has been retrieved for each voxel/vertex, it can be deconvolved from time series or one can map shape parameters everywhere in brain and use it as pathophysiological indicator. Input can be 2D GIfTI, 3D or 4D NIfTI images, but also on time series matrices/vectors. Output are three HRF shape parameters for each voxel/vertex, plus deconvolved time series, and number of retrieved pseudo events. All can be written back to GIfTI or NIfTI images.
Proper citation: Resting State Hemodynamic Response Function Retrieval and Deconvolution (RRID:SCR_023663) Copy
http://wego.genomics.org.cn/cgi-bin/wego/index.pl
Web Gene Ontology Annotation Plot (WEGO) is a simple but useful tool for plotting Gene Ontology (GO) annotation results. Different from other commercial software for chart creating, WEGO is designed to deal with the directed acyclic graph (DAG) structure of GO to facilitate histogram creation of GO annotation results. WEGO has been widely used in many important biological research projects, such as the rice genome project and the silkworm genome project. It has become one of the useful tools for downstream gene annotation analysis, especially when performing comparative genomics tasks. Platform: Online tool
Proper citation: WEGO - Web Gene Ontology Annotation Plot (RRID:SCR_005827) Copy
http://hdock.phys.hust.edu.cn/
Web server for protein-protein and protein-DNA/RNA docking based on hybrid strategy. With input information for receptor and ligand molecules either amino acid sequences or Protein Data Bank structures, the server automatically predicts their interaction through hybrid algorithm of template-based and template-free docking.
Proper citation: HDOCK server (RRID:SCR_024799) Copy
Web server as meta-predictor for phase-separating proteins. Displays proteome-level quantiles of different features, thus profiling PS propensity and providing crucial information for identification of candidate proteins.
Proper citation: PhaSePred (RRID:SCR_024969) Copy
http://www.atcgn.com:8080/quarTeT/home.html
Web toolkit for studies of large scale T2T genomes. Collection of tools designed for T2T genome assembly and characterization, including reference guided genome assembly, ultra long sequence based gap filling, telomere identification, and de novo centromere prediction. Includes four modules: AssemblyMapper, GapFiller, TeloExplorer, and CentroMiner. Modules can be used alone or in combination with each other for T2T genome assembly and characterization.
Proper citation: quarTeT (RRID:SCR_025258) Copy
https://github.com/xiaochuanle/NECAT
Software error correction and de-novo assembly tool for Nanopore long noisy reads. Nanopore data assembler.
Proper citation: NECAT (RRID:SCR_025350) Copy
https://www.uii-ai.com/research.html
AI-powered integrated research platform for one-stop analysis of medical images. Provides advanced functionality such as automatic segmentation, registration, and classification for variety of application domains. Has major merits including Advanced built-in algorithms applicable to multiple imaging modalities (i.e., CT, MR, PET, DR), diseases (i.e., tumor, neurodegenerative disease, pneumonia), and applications (i.e., diagnosis, treatment planning, follow-up); Iterative deep learning-based training strategy for fast delineation of ROIs of large-scale datasets, thereby saving clinicians' time and obtaining novel and more robust models; Modular architecture with customization and extensibility, where plugins can be designed for specific purposes.
Proper citation: uAI Research Portal (RRID:SCR_025870) Copy
https://cadd.labshare.cn/cb-dock2/php/index.php
Web server for protein-ligand blind docking, integrating cavity detection, docking and homologous template fitting. Given the three-dimensional structure of protein and ligand, can predict their binding sites and affinity for computer-aided drug discovery.
Proper citation: CB-dock2 (RRID:SCR_026134) Copy
https://github.com/PaulingLiu/ROGUE
Software tool as entropy-based metric for assessing purity of single cell populations. Used to accurately quantify purity of identified cell clusters.
Proper citation: ROGUE (RRID:SCR_026568) Copy
https://bioconductor.org/packages/release/bioc/html/DOSE.html
Software R package for disease ontology semantic and enrichment analysis.
Proper citation: DOSE (RRID:SCR_027408) Copy
https://github.com/zhongguojie1998/CSOmap
Software tool for reconstruction of cell spatial organization from single-cell RNA sequencing data based on ligand-receptor mediated self-assembly. Infers cellular spatial organization from scRNA-seq by modeling ligand–receptor-mediated self-assembly. It constructs 3D pseudo-space and quantifies cell–cell interactions for downstream visualization and hypothesis testing.
Proper citation: CSOmap (RRID:SCR_027636) Copy
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