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http://ligand-expo.rutgers.edu/

An integrated data resource for finding chemical and structural information about small molecules bound to proteins and nucleic acids within the structure entries of the Protein Data Bank. Tools are provided to search the PDB dictionary for chemical components, to identify structure entries containing particular small molecules, and to download the 3D structures of the small molecule components in the PDB entry. A sketch tool is also provided for building new chemical definitions from reported PDB chemical components.

Proper citation: Ligand Expo (RRID:SCR_006636) Copy   

•   Source: SciCrunch Registry

http://www.peptideatlas.org

Multi-organism, publicly accessible compendium of peptides identified in a large set of tandem mass spectrometry proteomics experiments. Mass spectrometer output files are collected for human, mouse, yeast, and several other organisms, and searched using the latest search engines and protein sequences. All results of sequence and spectral library searching are subsequently processed through the Trans Proteomic Pipeline to derive a probability of correct identification for all results in a uniform manner to insure a high quality database, along with false discovery rates at the whole atlas level. The raw data, search results, and full builds can be downloaded for other uses. All results of sequence searching are processed through PeptideProphet to derive a probability of correct identification for all results in a uniform manner ensuring a high quality database. All peptides are mapped to Ensembl and can be viewed as custom tracks on the Ensembl genome browser. The long term goal of the project is full annotation of eukaryotic genomes through a thorough validation of expressed proteins. The PeptideAtlas provides a method and a framework to accommodate proteome information coming from high-throughput proteomics technologies. The online database administers experimental data in the public domain. You are encouraged to contribute to the database.

Proper citation: PeptideAtlas (RRID:SCR_006783) Copy   

•   Source: SciCrunch Registry

http://cebs.niehs.nih.gov

Repository for toxicogenomics data, including study design and timeline, clinical chemistry and histopathology findings and microarray and proteomics data. Data derived from studies of chemicals and of genetic alterations, and is compatible with clinical and environmental studies. Data relating to environmental health, pharmacology, and toxicology. It is not necessary to have microarray data, but study design and phenotypic anchoring data are required.CEBS contains raw microarray data collected in accordance with MIAME guidelines and provides tools for data selection, pre-processing and analysis resulting in annotated lists of genes of interest. Biomedical Investigation Database is another component of CEBS system. used to load and curate study data prior to export to CEBS, in addition to capturing and displaying novel data types such as PCR data, or additional fields of interest, including those defined by the HESI Toxicogenomics Committee. BID has been shared with Health Canada and the US Environmental Protection Agency.

Proper citation: Chemical Effects in Biological Systems (CEBS) (RRID:SCR_006778) Copy   

•   Source: SciCrunch Registry

http://www.berkeleybop.org/

The BBOP, located at the Lawrence Berkeley National Labs, is a diverse group of scientific researchers and software engineers dedicated to developing tools and applying computational technologies to solve biological problems. Members of the group contribute to a number of projects, including the Gene Ontology, OBO Foundry, the Phenotypic Quality Ontology, modENCODE, and the Generic Model Organism Database Project. Our group is focused on the development, use, and integration of ontolgies into biological data analysis. Software written or maintained by BBOP is accessible through the site.

Proper citation: Berkeley Bioinformatics Open-Source Projects (RRID:SCR_006704) Copy   

•   Source: SciCrunch Registry

http://redfly.ccr.buffalo.edu

Curated collection of known Drosophila transcriptional cis-regulatory modules (CRMs) and transcription factor binding sites (TFBSs). Includes experimentally verified fly regulatory elements along with their DNA sequence, associated genes, and expression patterns they direct. Submission of experimentally verified cis-regulatory elements that are not included in REDfly database are welcome.

Proper citation: REDfly Regulatory Element Database for Drosophilia (RRID:SCR_006790) Copy   

•   Source: SciCrunch Registry

https://omictools.com/l2l-tool

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented on August 26, 2019.

Database of published microarray gene expression data, and a software tool for comparing that published data to a user''''s own microarray results. It is very simple to use - all you need is a web browser and a list of the probes that went up or down in your experiment. If you find L2L useful please consider contributing your published data to the L2L Microarray Database in the form of list files. L2L finds true biological patterns in gene expression data by systematically comparing your own list of genes to lists of genes that have been experimentally determined to be co-expressed in response to a particular stimulus - in other words, published lists of microarray results. The patterns it finds can point to the underlying disease process or affected molecular function that actually generated the observed changed in gene expression. Its insights are far more systematic than critical gene analyses, and more biologically relevant than pure Gene Ontology-based analyses. The publications included in the L2L MDB initially reflected topics thought to be related to Cockayne syndrome: aging, cancer, and DNA damage. Since then, the scope of the publications included has expanded considerably, to include chromatin structure, immune and inflammatory mediators, the hypoxic response, adipogenesis, growth factors, hormones, cell cycle regulators, and others. Despite the parochial origins of the database, the wide range of topics covered will make L2L of general interest to any investigator using microarrays to study human biology. In addition to the L2L Microarray Database, L2L contains three sets of lists derived from Gene Ontology categories: Biological Process, Cellular Component, and Molecular Function. As with the L2L MDB, each GO sub-category is represented by a text file that contains annotation information and a list of the HUGO symbols of the genes assigned to that sub-category or any of its descendants. You don''''t need to download L2L to use it to analyze your microarray data. There is an easy-to-use web-based analysis tool, and you have the option of downloading your results so you can view them at any time on your own computer, using any web browser. However, if you prefer, the entire L2L project, and all of its components, can be downloaded from the download page. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: L2L Microarray Analysis Tool (RRID:SCR_013440) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/nusdast

A repository of schizophrenia neuroimaging data collected from over 450 individuals with schizophrenia, healthy controls and their respective siblings, most with 2-year longitudinal follow-up. The data include neuroimaging data, cognitive data, clinical data, and genetic data.

Proper citation: Northwestern University Schizophrenia Data and Software Tool (NUSDAST) (RRID:SCR_014153) Copy   

•   Source: SciCrunch Registry

http://zhanglab.ccmb.med.umich.edu/I-TASSER/

Web server as integrated platform for automated protein structure and function prediction. Used for protein 3D structure prediction. Resource for automated protein structure prediction and structure-based function annotation.

Proper citation: I-TASSER (RRID:SCR_014627) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/biomodels-main/

Repository of mathematical models of biological and biomedical systems. Hosts selection of existing literature based physiologically and pharmaceutically relevant mechanistic models in standard formats. Features programmatic access via Web Services. Each model is curated to verify that it corresponds to reference publication and gives proper numerical results. Curators also annotate components of models with terms from controlled vocabularies and links to other relevant data resources allowing users to search accurately for models they need. Models can be retrieved in SBML format and import/export facilities are being developed to extend spectrum of formats supported by resource.

Proper citation: BioModels (RRID:SCR_001993) Copy   

•   Source: SciCrunch Registry

http://www.pathwaycommons.org/pc

Database of publicly available pathways from multiple organisms and multiple sources represented in a common language. Pathways include biochemical reactions, complex assembly, transport and catalysis events, and physical interactions involving proteins, DNA, RNA, small molecules and complexes. Pathways were downloaded directly from source databases. Each source pathway database has been created differently, some by manual extraction of pathway information from the literature and some by computational prediction. Pathway Commons provides a filtering mechanism to allow the user to view only chosen subsets of information, such as only the manually curated subset. The quality of Pathway Commons pathways is dependent on the quality of the pathways from source databases. Pathway Commons aims to collect and integrate all public pathway data available in standard formats. It currently contains data from nine databases with over 1,668 pathways, 442,182 interactions,414 organisms and will be continually expanded and updated. (April 2013)

Proper citation: Pathway Commons (RRID:SCR_002103) Copy   

•   Source: SciCrunch Registry

http://www.genenetwork.org/

Web platform that provides access to data and tools to study complex networks of genes, molecules, and higher order gene function and phenotypes. Sequence data (SNPs) and transcriptome data sets (expression genetic or eQTL data sets). Quantitative trait locus (QTL) mapping module that is built into GN is optimized for fast on-line analysis of traits that are controlled by combinations of gene variants and environmental factors. Used to study humans, mice (BXD, AXB, LXS, etc.), rats (HXB), Drosophila, and plant species (barley and Arabidopsis). Users are welcome to enter their own private data.

Proper citation: GeneNetwork (RRID:SCR_002388) Copy   

•   Source: SciCrunch Registry

https://github.com/jbelyeu/SV-plaudit

Software for rapidly curating structural variant (SVs) predictions. SV-plaudit provides a pipeline for creating image views of genomic intervals, automatically storing them in the cloud, deploying a website to view/score them, and retrieving scores for analysis.

Proper citation: SV-plaudit (RRID:SCR_016285) Copy   

•   Source: SciCrunch Registry

https://hub.docker.com/r/biodepot/star-for-criu/

Software as an Hot Start software container for STAR alignment using CRIU (Checkpoint Restore in Userspace) tool to freeze the running container. Can be deployed to align RNA sequencing data. Used in the processing of biomedical big data for better reproducibility and reliability.

Proper citation: star-for-criu (RRID:SCR_016294) Copy   

•   Source: SciCrunch Registry

https://emcore.ucsf.edu/cryoem-software

Software tool for anisotropic correction of beam-induced motion for improved cryo-electron microscopy. Used to describe the sample motion as a local deformation that varies smoothly throughout the exposure. A program running on Linux.

Proper citation: MotionCor2 (RRID:SCR_016499) Copy   

•   Source: SciCrunch Registry

https://github.com/fbreitwieser/pavian

Software R package for interactive analysis of metagenomics classification results with a special focus on infectious disease diagnosis. Used for analyzing and visualization of metagenomics classification results from classifiers such as Kraken, Centrifuge and MetaPhlAn. Provides an alignment viewer for validation of matches to a particular genome.

Proper citation: Pavian (RRID:SCR_016679) Copy   

•   Source: SciCrunch Registry

https://github.com/WilsonSayresLab/XYalign

Software tool for identifying, understanding, and correcting technical biases on the sex chromosomes in next generation sequencing data.

Proper citation: XYalign (RRID:SCR_016661) Copy   

•   Source: SciCrunch Registry

http://www.ccb.jhu.edu/software/centrifuge/

Software for rapid and sensitive classification of metagenomic sequences. Used for the classification of DNA sequences from microbial samples and analysis of large metagenomics data sets on conventional desktop computers.

Proper citation: Centrifuge Classifier (RRID:SCR_016665) Copy   

•   Source: SciCrunch Registry

https://knoweng.org

Part of the NIH Big Data to Knowledge (BD2K) Initiative. One of 11 Centers of Excellence in Big Data Computing. Platform for genomics data analysis where user-supplied data sets will be analyzed in the context of existing knowledge. E-science framework for genomics where biomedical scientists will have access to powerful methods of data mining, network mining, and machine learning to extract knowledge out of genomics data.

Proper citation: KnowEnG (RRID:SCR_016875) Copy   

•   Source: SciCrunch Registry

https://csgid.org/csgid/metal_sites

Metal binding site validation server. Used for systematic inspection of the metal-binding architectures in macromolecular structures. The validation parameters that CMM examines cover the entire binding environment of the metal ion, including the position, charge and type of atoms and residues surrounding the metal.

Proper citation: CheckMyMetal (RRID:SCR_016887) Copy   

•   Source: SciCrunch Registry

https://github.com/dpeerlab/phenograph

Software tool as clustering method designed for high dimensional single cell data. Algorithmically defines phenotypes in high dimensional single cell data. Used for large scale analysis of single cell heterogeneity.

Proper citation: Phenograph (RRID:SCR_016919) Copy   

•   Source: SciCrunch Registry