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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.

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On page 29 showing 561 ~ 580 out of 15,871 results
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  • RRID:SCR_006728

    This resource has 10+ mentions.

http://rulai.cshl.edu/splicetrap/

A statistic tool for quantifying exon inclusion ratios in paired-end RNA-seq data, with broad applications for the study of alternative splicing. SpliceTrap approaches to exon inclusion level estimation as a Bayesian inference problem. For every exon it quantifies the extent to which it is included, skipped or subjected to size variations due to alternative 3?/5? splice sites or Intron Retention. In addition, SpliceTrap can quantify alternative splicing within a single cellular condition, with no need of a background set of reads.

Proper citation: SpliceTrap (RRID:SCR_006728) Copy   


  • RRID:SCR_006646

    This resource has 10000+ mentions.

https://github.com/arq5x/bedtools2

A powerful toolset for genome arithmetic allowing one to address common genomics tasks such as finding feature overlaps and computing coverage. Bedtools allows one to intersect, merge, count, complement, and shuffle genomic intervals from multiple files in widely-used genomic file formats such as BAM, BED, GFF/GTF, VCF. While each individual tool is designed to do a relatively simple task (e.g., intersect two interval files), quite sophisticated analyses can be conducted by combining multiple bedtools operations on the UNIX command line.

Proper citation: BEDTools (RRID:SCR_006646) Copy   


  • RRID:SCR_006591

    This resource has 1+ mentions.

http://sourceforge.net/projects/niftysim/

A high-performance nonlinear finite element solver. A key feature is the option of GPU-based execution, which allows the solver to significantly out-perform equivalent commercial packages.

Proper citation: NiftySim (RRID:SCR_006591) Copy   


  • RRID:SCR_006627

    This resource has 1+ mentions.

https://wiki.nci.nih.gov/display/LexEVS/LexGrid

LexGrid (Lexical Grid) provides support for a distributed network of lexical resources such as terminologies and ontologies via standards-based tools, storage formats, and access/update mechanisms. The Lexical Grid Vision is for a distributed network of terminological resources. It is the foundation of the National Center for Biomedical Ontology BioPortal interface and web-services, and can parse OBO format, as well as other formats such as OWL. Currently, there are many terminologies and ontologies in existence. Just about every terminology has its own format, its own set of tools, and its own update mechanisms. The only thing that most of these pieces have in common with each other is their incompatibility. This makes it very hard to use these resources to their full potential. We have designed the Lexical Grid as a way to bridge terminologies and ontologies with a common set of tools, formats and update mechanisms. The Lexical Grid is: * accessible through a set of common APIs * joined through shared indices * online accessible * downloadable * loosely coupled * locally extendable * globally revised * available in web-space on web-time * cross-linked The realization of this vision requires three interlocking components, which are: * Standards - access methods and formats need to be published and openly available * Tools - standards based tools must be readily available * Content - commonly used terminologies have to be available for access and download Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: LexGrid (RRID:SCR_006627) Copy   


  • RRID:SCR_006700

    This resource has 1+ mentions.

http://www.alexaplatform.org/alexa_seq/index.htm

A method for using massively parallel paired-end transcriptome sequencing for ''alternative expression analysis''.

Proper citation: ALEXA-Seq (RRID:SCR_006700) Copy   


  • RRID:SCR_006657

    This resource has 10+ mentions.

http://sourceforge.net/projects/splicegrapher/

Software that predicts alternative splicing patterns and produces splice graphs that capture in a single structure the ways a gene''s exons may be assembled. It enhances gene models using evidence from next-generation sequencing and EST alignments.

Proper citation: SpliceGrapher (RRID:SCR_006657) Copy   


  • RRID:SCR_006653

    This resource has 1+ mentions.

http://www.bioconductor.org/packages/devel/bioc/html/ChIPXpress.html

A R package designed to improve ChIP-seq and ChIP-chip target gene ranking using publicly available gene expression data. It takes as input predicted transcription factor (TF) bound genes from ChIPx data and uses a corresponding database of gene expression profiles downloaded from NCBI GEO to rank the TF bound targets in order of which gene is most likely to be functional TF target.

Proper citation: ChIPXpress (RRID:SCR_006653) Copy   


  • RRID:SCR_006724

    This resource has 10000+ mentions.

https://www.promega.com/

An Antibody supplier

Proper citation: Promega (RRID:SCR_006724) Copy   


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

Web game that provides an innovative infrastructure for labeling to enable an alternative to expert raters for medical image labeling through statistical analysis of the collaborative efforts of many, minimally-trained raters. Statistical atlases of regional brain anatomy have proven to be extremely useful in characterizing the relationship between the structure and function of the human nervous system. Typically, an expert human rater manually examines each slice of a three-dimensional volume. This approach can be exceptionally time and resource intensive, so cost severely limits the clinical studies where subject-specific labeling is feasible. Methods for improved efficiency and reliability of manual labeling would be of immense benefit for clinical investigation into morphological correlates of brain function.

Proper citation: Web Game for Collaborative Labeling (RRID:SCR_006685) Copy   


  • RRID:SCR_006683

    This resource has 1+ mentions.

https://code.google.com/p/softsearch/

A sensitive structural variant (SV) detection software tool for Illumina paired-end next-generation sequencing data. It simultaneously utilizes soft-clipping and read-pair strategies for detecting SVs to increase sensitivity. Soft clips are proxies for split-reads that indicate part of the read maps to the reference genome, but the other part is not localized at the same place (e.g. breakpoint spanning reads). Discordant read-pairs refer to a read and its mate, where the insert size is greater (or less than) the expected distribution of the dataset ? or ? where the mapping orientation of the reads is unexpected (e.g. both on the same strand). SoftSearch looks for areas with soft-clipping in the genome that have discordant read pairs supporting the anomaly. Once areas with both these conditions are identified, the read and mate information is extracted directly from the BAM file containing the discordant reads, obviating the need for time-consuming and error-prone complex alignment strategies. Only a small number of soft-masked bases discordant read-pairs are necessary to identify an SV, which on their own would not be sufficient to make an SV call, thus highlighting SoftSearch?s improved sensitivity. SoftSearch is well suited to be ?plugged in? to most sequence analysis workflows, since it requires standard file inputs, such as a BAM file using almost any aligner and a reference genome FASTA file. Because SoftSearch requires soft-masked bases, the only requirement is that the aligner must have this functionality, which is usually turned on by default by many standard aligners (e.g. BWA, Novoalign, etc).

Proper citation: SoftSearch (RRID:SCR_006683) Copy   


  • RRID:SCR_006719

    This resource has 1+ mentions.

http://www.nactem.ac.uk/GREC/

A semantically annotated corpus of 240 MEDLINE abstracts (167 on the subject of E. coli species and 73 on the subject of the Human species) intended for training information extraction (IE) systems and/or resources which are used to extract events from biomedical literature. The corpus has been manually annotated with events relating to gene regulation by biologists. Each event is centered on either a verb (e.g. transcribe) or nominalized verb (e.g. transcription) and annotation consists of identifying, as exhaustively as possible, the structurally-related arguments of the verb or nominalized verb within the same sentence. Each event argument is then assigned the following information: * A semantic role from a fixed set of 13 roles which are tailored to the biomedical domain. * A biomedical concept type (where appropriate). The corpus in available for download in 2 formats: * A standoff format, based on the BioNLP'09 Shared Task format * An XML format, based on the GENIA event annotation format

Proper citation: GREC Corpus (RRID:SCR_006719) Copy   


  • RRID:SCR_006751

    This resource has 100+ mentions.

http://watson.nci.nih.gov/bioc_mirror/packages/2.11/bioc/html/EDASeq.html

Software for numerical and graphical summaries of RNA-Seq read data. Within-lane normalization procedures to adjust for GC-content effect (or other gene-level effects) on read counts: loess robust local regression, global-scaling, and full-quantile normalization (Risso et al., 2011). Between-lane normalization procedures to adjust for distributional differences between lanes (e.g., sequencing depth): global-scaling and full-quantile normalization (Bullard et al., 2010)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: EDASeq (RRID:SCR_006751) Copy   


http://sourceforge.net/projects/polgui/

An interface between MATLAB and the Polhemus Fastrak digitizer used to digitize fiducial locations and scalp EEG electrode locations. There are 5 versions all of which work under MATLAB R14 (on both linux and windows platforms), # polgui_ver1_r14 : works with 1 receiver (stylus pen) # polgui_ver2_r14 : works with 2 receivers (including the pen) # polgui_ver3_r14 : works with 3 receivers(including the pen) # polgui_ver4_r14 : works with 4 receivers (including the pen) # polgui_ver5_r14 : Generic version which works with 1/2/3/4 receivers (WARNING: Ver 5 might be buggy; not fully tested) Requirements: MATLAB R14 (Linux/Windows)

Proper citation: POLGUI - Matlab Polhemus Interface (RRID:SCR_006752) Copy   


  • RRID:SCR_006785

    This resource has 1+ mentions.

http://sourceforge.net/projects/mubiomics/

A set of scripts (mostly python) for processing reads generated by the Roche 454 or Illumina next-gen sequencing platforms. Included are quality control, read demultiplexing and microbiome characterisation scripts for use with usearch, pplacer and RDP classifier.

Proper citation: mubiomics (RRID:SCR_006785) Copy   


  • RRID:SCR_006813

    This resource has 100+ mentions.

http://www.bioconductor.org/packages/2.11/bioc/html/ShortRead.html

Software package for input, quality assessment and exploration of high-throughput sequence data. Used for input, quality assurance, and basic manipulation of `short read'' DNA sequences such as those produced by Solexa, 454, and related technologies, including exible import of common short read data formats.

Proper citation: ShortRead (RRID:SCR_006813) Copy   


  • RRID:SCR_006815

    This resource has 10+ mentions.

http://compbio.bccrc.ca/software/mutationseq/

A software suite using feature-based classifiers for somatic mutation prediction from paired tumour/normal next-generation sequencing data. mutationSeq has the advantages of integrating different features (e.g., base qualities, mapping qualities, strand bias, and tailed distance features), and validated somatic mutations to make predictions. Given paired normal/tumour bam files, mutationSeq will output the probability of each candidate site being somatic.

Proper citation: mutationSeq (RRID:SCR_006815) Copy   


http://www.uni-rostock.de/en/

Public university located in Rostock, Mecklenburg-Vorpommern, Germany. Founded in 1419.

Proper citation: University of Rostock; Mecklenburg-Vorpommern; Germany (RRID:SCR_006816) Copy   


  • RRID:SCR_006810

    This resource has 10+ mentions.

http://www.bioconductor.org/packages/2.12/bioc/html/RIPSeeker.html

A statistical software package for identifying protein-associated transcripts from RIP-seq experiments. Infer and discriminate RIP peaks from RIP-seq alignments using two-state HMM with negative binomial emission probability. While RIPSeeker is specifically tailored for RIP-seq data analysis, it also provides a suite of bioinformatics tools integrated within this self-contained software package comprehensively addressing issues ranging from post-alignments processing to visualization and annotation.

Proper citation: RIPSeeker (RRID:SCR_006810) Copy   


  • RRID:SCR_006779

    This resource has 10+ mentions.

http://biobricks.org/

The BioBricks Foundation (BBF) is dedicated to advancing synthetic biology to benefit all people and the planet. To achieve this, we must make engineering biology easier, safer, equitable, and more open. We do this in the following ways: by ensuring that the fundamental building blocks of synthetic biology are freely available for open innovation; by creating community, common values and shared standards; and by promoting biotechnology for all constructive interests. We envision a world in which scientists and engineers work together using BioBric parts freely available standardized biological parts to create safe, ethical solutions to the problems facing humanity. We envision synthetic biology as a force for good in the world. We see a future in which architecture, medicine, environmental remediation, agriculture, and many other fields are using the technology of synthetic biology. Our supporters are many and include corporations, individuals, institutions, foundations, government, corporations, and others. Currently, the BBF''s key programs include: * BIOFAB * BioBrick Public Agreement * Technical Standards Framework * Conferences and Workshops * BBF Global Network * OpenWetWare

Proper citation: BioBricks Foundation (RRID:SCR_006779) Copy   


  • RRID:SCR_006802

    This resource has 10000+ mentions.

https://www.peprotech.com/

An Antibody supplier

Proper citation: PeproTech (RRID:SCR_006802) Copy   



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