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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://cm.jefferson.edu/rna22/

Software tool as a pattern based algorithm for detecting microRNA binding sites and their corresponding microRNA and mRNA complexes. Allows interactive exploration and visualization of miRNA target predictions. Permits link-out to external expression repositories and databases.

Proper citation: RNA22 (RRID:SCR_016507) Copy   

•   Source: SciCrunch Registry

https://tbportals.niaid.nih.gov

Web based open access platform for global drug resistant tuberculosis data sharing and analysis. The NIAID TB Portals program and consortium of clinicians and scientists from countries with a heavy burden of TB, especially drug resistant TB, to collect TB data.

Proper citation: TB PORTALS (RRID:SCR_016594) Copy   

•   Source: SciCrunch Registry

https://triage.niaid.nih.gov

Platform to facilitate prediction, analysis, and hypothesis generation from genome wide perturbation studies like those designed with RNAi and CRISPR technologies.

Proper citation: TRIAGE (RRID:SCR_016609) Copy   

•   Source: SciCrunch Registry

https://www.ncbi.nlm.nih.gov/projects/mutagene/

Software tool to explore and analyze mutagenic factors leading to tumors to decipher cancer genetic heterogeneity.

Proper citation: MutaGene (RRID:SCR_016574) Copy   

•   Source: SciCrunch Registry

https://commonfund.nih.gov/hubmap

Project to facilitate research on single cells within tissues by supporting data generation and technology development to explore the relationship between cellular organization and function, as well as variability in normal tissue organization at the level of individual cells. Framework for functional mapping the human body with cellular resolution.Designed to support diverse spatial and non-spatial omics and imaging data types and to integrate with a wide range of analysis workflows.

Proper citation: The Human BioMolecular Atlas Program (RRID:SCR_016922) Copy   

•   Source: SciCrunch Registry

https://blake.bcm.edu/emanwiki/EMAN2

Software suite for processing data from transmission electron microscopes. Used in supercomputing facilities as a test application for large-scale computing. Used for single particle reconstruction, helical reconstruction, 2-D crystallography and whole-cell tomography.

Proper citation: EMAN (RRID:SCR_016867) 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

http://homer.ucsd.edu/

Software tools for Motif Discovery and next-gen sequencing analysis. Used for analyzing ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and numerous other types of functional genomics sequencing data sets. Collection of command line programs for unix style operating systems written in Perl and C++.

Proper citation: HOMER (RRID:SCR_010881) Copy   

•   Source: SciCrunch Registry

http://www.wwpdb.org/

Public global Protein Data Bank archive of macromolecular structural data overseen by organizations that act as deposition, data processing and distribution centers for PDB data. Members are: RCSB PDB (USA), PDBe (Europe) and PDBj (Japan), and BMRB (USA). This site provides information about services provided by individual member organizations and about projects undertaken by wwPDB. Data available via websites of its member organizations.

Proper citation: Worldwide Protein Data Bank (wwPDB) (RRID:SCR_006555) Copy   

•   Source: SciCrunch Registry

http://www.physionet.org/physiobank/database/gaitpdb/

Database that contains measures of gait from 93 patients with idiopathic PD (mean age: 66.3 years; 63% men), and 73 healthy controls (mean age: 66.3 years; 55% men). The database includes the vertical ground reaction force records of subjects as they walked at their usual, self-selected pace for approximately 2 minutes on level ground. Underneath each foot were 8 sensors (Ultraflex Computer Dyno Graphy, Infotronic Inc.) that measure force (in Newtons) as a function of time. The output of each of these 16 sensors has been digitized and recorded at 100 samples per second, and the records also include two signals that reflect the sum of the 8 sensor outputs for each foot. This database also includes demographic information, measures of disease severity (i.e., using the Hoehn & Yahr staging and/or the Unified Parkinson's Disease Rating Scale) and other related measures (available in HTML or xls spreadsheet format). A subset of the database includes measures recorded as subjects performed a second task (serial 7 subtractions) while walking, which shows excerpts of swing time series from a patient with PD and a control subject, under usual walking conditions and when performing serial 7 subtractions. Under usual walking conditions, variability is larger in the patient with PD (Coefficient of Variation = 2.7%), compared to the control subject (CV = 1.3%). Variability increases during dual tasking in the subject with PD (CV = 6.5%), but not in the control subject (CV = 1.2%).

Proper citation: Gait in Parkinson's Disease (RRID:SCR_006891) Copy   

•   Source: SciCrunch Registry

http://tulane.edu/som/regenmed/services/index.cfm

The Stem Cell Research and Regenerative Medicine''s Tissue Culture Core provides cells for research use within the department, as well as for distribution to other facilities. The core obtains hMSCs from bone marrow donor samples and expands these cells for research use. The hMSC''s are also characterized for bone, fat and cartilage differentiation, and are stored on site for use. The Tissue Culture Core also handles the expansion and characterization of mouse and rat MSC''s. The animal cells are cultured in a separate area, and never interact with human derived cells. We also have a supply of hMSC''s marked with GFP+, Mito Red and Mito Blue available.

Proper citation: Tulane Stem Cell Research and Regenerative Medicine Tissue Culture Core (RRID:SCR_007342) Copy   

•   Source: SciCrunch Registry

http://www.nhpreagents.org

Center that facilitates the optimal use of nonhuman primate models in biomedical research by identifying, developing, characterizing and producing reagents for monitoring or modulating immune responses. They distribute non-human primate-specific antibodies for in vitro diagnostics, as well as develop and produce primate recombinant antibodies for in vivo cell depletion or modulating immune responses.

Proper citation: Nonhuman Primate Reagent Resource (RRID:SCR_012986) Copy   

•   Source: SciCrunch Registry

http://www.ncbcs.org/

The NCBCs are a set of networked computation core facilities for biomedical infrastructure funded under the NIH Common Fund, the National Program of Excellence in Biomedical Computing (NPEBC). There are seven funded Centers that cover systems biology, image processing, biophysical modeling, biomedical ontologies, information integration, and tools for gene-phenotype and disease analysis. The centers will create innovative software programs and other tools that enable the biomedical community to integrate, analyze, model, simulate, and share data on human health and disease. Each Center has Cores that are focused on (1) computational science, (2) biomedical computational science and (3) driving biological projects whose intent is to drive the interaction between computational and biomedical computational science. In addition to the Centers, the NIH has a number of active program announcements to develop collaborations with the biomedical research community��this includes announcements from the Biomedical Information Science and Technology Initiative (BISTI) and the Program for Collaborations with National Centers for Biomedical Computing. There are numerous efforts in education and training that emanate from the Centers and there is an annual all hands meeting.

Proper citation: National Centers for Biomedical Computing (RRID:SCR_010635) Copy   

•   Source: SciCrunch Registry

https://www.ebi.ac.uk/intact/complex/#annotations:fIzBXhJPEeej78Pl6R0ScA

Database and encyclopaedic resource of macromolecular complexes found in key model organisms from scientific literature. Data includes protein-only complexes, protein-small molecules, and protein-nucleic acid complexes. The information within the portal is manually curated and available for download.

Proper citation: Complex Portal (RRID:SCR_015038) Copy   

•   Source: SciCrunch Registry

https://drugs.ncats.io/

Portal of NCATS (the National Center for Advancing Translational Sciences) for drug development information including:US approved drugs, marketed drugs, investigational drugs. Provides manually curated data supplied by the FDA and private companies. Provides drugs marketing and regulatory status, drug ingredient definitions, biological activity and clinical use.

Proper citation: Inxight (RRID:SCR_016490) Copy   

•   Source: SciCrunch Registry

https://www.niaid.nih.gov/about/cyber-infrastructure-computational-biology-contacts

Office of Cyber Infrastructure and Computational Biology of NIAID.

Proper citation: OCICB (RRID:SCR_016597) Copy   

•   Source: SciCrunch Registry

http://integromedb.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 26, 2016. Search engine that integrates over 100 curated and publicly contributed data sources and provides integrated views on the genomic, proteomic, transcriptomic, genetic and functional information currently available. Information featured in the database includes gene function, orthologies, gene expression, pathways and protein-protein interactions, mutations and SNPs, disease relationships, related drugs and compounds.

Proper citation: IntegromeDB (RRID:SCR_004620) Copy   

•   Source: SciCrunch Registry

http://www.phenologs.org/

Database for identifying orthologous phenotypes (phenologs). Mapping between genotype and phenotype is often non-obvious, complicating prediction of genes underlying specific phenotypes. This problem can be addressed through comparative analyses of phenotypes. We define phenologs based upon overlapping sets of orthologous genes associated with each phenotype. Comparisons of >189,000 human, mouse, yeast, and worm gene-phenotype associations reveal many significant phenologs, including novel non-obvious human disease models. For example, phenologs suggest a yeast model for mammalian angiogenesis defects and an invertebrate model for vertebrate neural tube birth defects. Phenologs thus create a rich framework for comparing mutational phenotypes, identify adaptive reuse of gene systems, and suggest new disease genes. To search for phenologs, go to the basic search page and enter a list of genes in the box provided, using Entrez gene identifiers for mouse/human genes, locus ids for yeast (e.g., YHR200W), or sequence names for worm (e.g., B0205.3). It is expected that this list of genes will all be associated with a particular system, trait, mutational phenotype, or disease. The search will return all identified model organism/human mutational phenotypes that show any overlap with the input set of the genes, ranked according to their hypergeometric probability scores. Clicking on a particular phenolog will result in a list of genes associated with the phenotype, from which potential new candidate genes can identified. Currently known phenotypes in the database are available from the link labeled ''Find phenotypes'', where the associated gene can be submitted as queries, or alternately, can be searched directly from the link provided.

Proper citation: Phenologs (RRID:SCR_005529) Copy   

•   Source: SciCrunch Registry

http://bigg.ucsd.edu/

A knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest.

Proper citation: BiGG Database (RRID:SCR_005809) Copy   

•   Source: SciCrunch Registry