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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://www.adinstruments.com/products/software/modules/neuro_explorer.php
THIS RESOURCE IS NO LONGER IN SERVICE, documented on May 19, 2018; A provider of computer-based data acquisition and analysis systems for life science. Products enable users to record and analyze life science data quickly and efficiently. ADInstruments product range is based on the PowerLab data acquisition system with LabChart software. The PowerLab system (also MacLab) is used in universities, hospitals, research institutes, pharmaceutical companies, contract research organizations and other private industry research sectors.
Proper citation: ADInstruments - Data Acquisition Systems for Life Science (RRID:SCR_001620) Copy
https://github.com/katiasmirn/PERFect#perfect-permutation-filtering-package-in-r
Software R package as filtering test for microbiome data. Permutation filtering approach to address two unsolved problems in microbiome data processing: (i) define and quantify loss due to filtering by implementing thresholds and (ii) introduce and evaluate a permutation test for filtering loss to provide a measure of excessive filtering.
Proper citation: PERFect (RRID:SCR_024682) Copy
http://www.nematodes.org/bioinformatics/trace2dbEST/
Software tool to process raw sequenceing chromatograph trace files from EST projects into quality checked sequences, ready for submission to dbEST.
Proper citation: trace2dbEST (RRID:SCR_024386) Copy
Platform for researchers to economically create and manage digital health programs. Platform built for research management and digital interventions. Helps researchers collect data and engage participants.
Proper citation: Pattern Health Digital Research Platform (RRID:SCR_024468) Copy
https://www.sdsc.edu/services/hpc/tscc/index.html
Provides advanced computing resources and services to support needs of UC San Diego research community. In addition, researchers from other academic institutions and industries can also participate in this research computing program. TSCC operates on two different computing models – Condo (a system purchase model) and Hotel (a pay-as-you-go model) to support broad range of research computing workloads including traditional HPC, HTC, and emerging big data pipelines.
Proper citation: Triton Shared Computing Cluster (RRID:SCR_024640) Copy
http://www.ccmb.med.umich.edu/ccdu/SNPAAMapper
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 19,2025. A downstream variant annotation program that can effectively classify variants by region (e.g. exon, intron, etc), predict amino acid change type (e.g. synonymous, non-synonymous mutation, etc), and prioritize mutation effects (e.g. CDS versus 5?UTR, etc). Major features: * The pipeline accepts the VCF (Variant Call Format) input file in tab-delimited format and processes the vcf input file containing all cases (G5, lowFreq, and novel) * The variant mapping step has the option of letting users select whether they want to report the bp distance between each identified intron variant and its nearby exon * The pipeline can deal with VCF files called by different SAMTools versions (0.1.18 and older ones) and also offers flexibility in dealing with vcf input files generated using SAMTools with two or three samples * The spreadsheet result file contains full protein sequences for both ref and alt alleles, which makes it easier for downstream protein structure/function analysis tools to take
Proper citation: SNPAAMapper (RRID:SCR_002012) Copy
http://sourceforge.net/apps/mediawiki/mummergpu/index.php?title=MUMmerGPU
Software tool as high throughput DNA sequence alignment program that runs on nVidia G80-class GPUs. Aligns sequences in parallel on video card to accelerate widely used serial CPU program MUMmer.
Proper citation: MUMmerGPU (RRID:SCR_001200) Copy
http://www.bioinformatics.org/wiki/BioWiki
A meta-list that is a compilation of other biology related wikipedia pages. These listings include the wiki name, description, year of inception, pages, new pages, users, active users, new edits, and wiki logo. The table can also be downloaded in a csv formatted table.
Proper citation: BioWiki (RRID:SCR_000629) Copy
A resource for information pertaining to methodologies, tools and technologies of gene expression. The website offers resources for sequence analysis, database services, and other technologies of gene expression and regulation.
Proper citation: IFTI-Mirage (RRID:SCR_000505) Copy
http://www.atsdr.cdc.gov/toxprofiles
A database of information about contaminants found at hazardous waste sites. The toxicological profiles are cataloged by chemical with the NTIS order number.
Proper citation: CDC Toxprofiles (RRID:SCR_000900) Copy
http://www.bioconductor.org/packages/release/bioc/html/HTqPCR.html
Software package for the analysis of Ct values from high throughput quantitative real-time PCR (qPCR) assays across multiple conditions or replicates. The input data can be from spatially-defined formats such ABI TaqMan Low Density Arrays or OpenArray; LightCycler from Roche Applied Science; the CFX plates from Bio-Rad Laboratories; conventional 96- or 384-well plates; or microfluidic devices such as the Dynamic Arrays from Fluidigm Corporation. HTqPCR handles data loading, quality assessment, normalization, visualization and parametric or non-parametric testing for statistical significance in Ct values between features (e.g. genes, microRNAs).
Proper citation: HTqPCR (RRID:SCR_003375) Copy
Mindboggle (http://mindboggle.info) is open source software for analyzing the shapes of brain structures from human MRI data. The following publication in PLoS Computational Biology documents and evaluates the software: Klein A, Ghosh SS, Bao FS, Giard J, Hame Y, Stavsky E, Lee N, Rossa B, Reuter M, Neto EC, Keshavan A. (2017) Mindboggling morphometry of human brains. PLoS Computational Biology 13(3): e1005350. doi:10.1371/journal.pcbi.1005350
Proper citation: Mindboggle (RRID:SCR_002438) Copy
Project portal's database of protein-ligand data sets provided by pharmaceutical partners that provide atomic details of drug mechanisms that will be used to improve computer-aided drug-design methods and thus accelerate drug discovery. The project aims to help companies release the high-quality data they have generated, which has incredible value to researchers working to improve methods of computer-aided drug discovery. Everyone stands to benefit from the ability to develop new medications more quickly and inexpensively. What computational chemists globally are trying to do is to make faster, more accurate, more predictive programs to speed up the process. Part of their mission is to engage the community in these challenges to test newly developed predictive algorithms.
Proper citation: Drug Design Data Resource (RRID:SCR_000497) Copy
http://www.nitrc.org/projects/surfacestat/
Software tool for performing a per vertex statistical analysis across a population. The underlying statistical framework uses the R language.
Proper citation: BRAINSSurfaceStats (RRID:SCR_002582) Copy
http://cran.r-project.org/web/packages/NanoStringNorm/
Software package for normalizing, diagnostics and visualization of NanoString nCounter data. Key features include an extensible environment for method comparison and new algorithm development, integrated gene and sample diagnostics, and facilitated downstream statistical analysis.
Proper citation: NanoStringNorm (RRID:SCR_003382) Copy
http://sourceforge.net/projects/skewer/
Software program for adapter trimming that is specially designed for processing Illumina paired-end sequences.
Proper citation: skewer (RRID:SCR_001151) Copy
http://discover.nci.nih.gov/gominer/
GoMiner is a tool for biological interpretation of "omic" data including data from gene expression microarrays. Omic experiments often generate lists of dozens or hundreds of genes that differ in expression between samples, raising the question, What does it all mean biologically? To answer this question, GoMiner leverages the Gene Ontology (GO) to identify the biological processes, functions and components represented in these lists. Instead of analyzing microarray results with a gene-by-gene approach, GoMiner classifies the genes into biologically coherent categories and assesses these categories. The insights gained through GoMiner can generate hypotheses to guide additional research. GoMiner displays the genes within the framework of the Gene Ontology hierarchy in two ways: * In the form of a tree, similar to that in AmiGO * In the form of a "Directed Acyclic Graph" (DAG) The program also provides: * Quantitative and statistical analysis * Seamless integration with important public databases GoMiner uses the databases provided by the GO Consortium. These databases combine information from a number of different consortium participants, include information from many different organisms and data sources, and are referenced using a variety of different gene product identification approaches.
Proper citation: GoMiner (RRID:SCR_002360) Copy
Nonprofit, government-funded research organization dedicated to the enhancement of medical research and the improvement of health care in Taiwan. Research interests include both aspects of basic biomedical sciences and specific diseases such as cancer, mental disorders and infectious diseases. The institute is meant to provide direction to national science and technology development in health and medical care, educate young scientists and physicians, establish an objective and fair system for research, and promoting domestic and international cooperation.
Proper citation: National Health Research Institutes; Taipei; Taiwan (RRID:SCR_000335) Copy
http://embryo.soad.umich.edu/animal/home.html
THIS RESOURCE IS NO LONGER IN SERVICE, documented on February 14, 2013. A multidimensional, digital atlas based on magnetic resonance images of normal mouse embryos from 9.5 days after conception (E9) to the newborn (P0). The images include surface views and cross-sectional views from the transverse, coronal, and sagittal planes for each embryo. Several movies have also been included to demonstrate growth of the embryos and to present a variety of visualization tools available for studying and documenting embryonic anatomy. These images are organized as a reference for educators and researchers who want to understand better the embryological anatomy of their own specimens and to understand how their images relate to the whole embryo at many stages of development.
Proper citation: Magnetic Resonance Microscopy of Mouse Embryo Specimens (RRID:SCR_001145) Copy
http://bioinformatics.biol.rug.nl/standalone/fiva/
Functional Information Viewer and Analyzer (FIVA) aids researchers in the prokaryotic community to quickly identify relevant biological processes following transcriptome analysis. Our software is able to assist in functional profiling of large sets of genes and generates a comprehensive overview of affected biological processes. Currently, seven different modules containing functional information have been implemented: (i) gene regulatory interactions, (ii) cluster of orthologous groups (COG) of proteins, (iii) gene ontologies (GO), (iv) metabolic pathways (v) Swiss Prot keywords, (vi) InterPro domains - and (vii) generic functional categories. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: FIVA - Functional Information Viewer and Analyzer (RRID:SCR_005776) Copy
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