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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://sourceforge.net/projects/bio-rainbow/
Software developed to provide an ultra-fast and memory-efficient solution to clustering and assembling short reads produced by RAD-seq.
Proper citation: Rainbow (RRID:SCR_002724) Copy
Database that collects, integrates and links all relevant primary information from the GABI plant genome research projects and makes them accessible via internet. Its purpose is to support plant genome research in Germany, to yield information about commercial important plant genomes, and to establish a scientific network within plant genomic research.
GreenCards is the main interface for text based retrieval of sequence, SNP, mapping data etc. Sharing and interchange of data among collaborating research groups, industry and the patent- and licensing agency are facilitated.
* GreenCards: Text based search for sequence, mapping, SNP data etc. * Maps: Visualization of genetic or physical maps. * BLAST: Secure BLAST search against different public databases or non-public sequence data stored in GabiPD. * Proteomics: View interactive 2D-gels and view or download information for identified protein spots. Registered users can submit data via secure file upload.
Proper citation: Gabi Primary Database (RRID:SCR_002755) Copy
https://github.com/GiBacci/StreamingTrim/
A DNA reads trimming software, written in Java, with which researchers are able to analyse the quality of DNA sequences in fastq files and to search for low-quality zones in a very conservative way.
Proper citation: StreamingTrim (RRID:SCR_002922) Copy
Portal that supports Ambystoma-related research and educational efforts. It is composed of several resources: Salamander Genome Project, Ambystoma EST Database, Ambystoma Gene Collection, Ambystoma Map and Marker Collection, Ambystoma Genetic Stock Center, and Ambystoma Research Coordination Network.
Proper citation: Sal-Site (RRID:SCR_002850) Copy
Computational biology research at Memorial Sloan-Kettering Cancer Center (MSKCC) pursues computational biology research projects and the development of bioinformatics resources in the areas of: sequence-structure analysis; gene regulation; molecular pathways and networks, and diagnostic and prognostic indicators. The mission of cBio is to move the theoretical methods and genome-scale data resources of computational biology into everyday laboratory practice and use, and is reflected in the organization of cBio into research and service components ~ the intention being that new computational methods created through the process of scientific inquiry should be generalized and supported as open-source and shared community resources. Faculty from cBio participate in graduate training provided through the following graduate programs: * Gerstner Sloan-Kettering Graduate School of Biomedical Sciences * Graduate Training Program in Computational Biology and Medicine Integral to much of the research and service work performed by cBio is the creation and use of software tools and data resources. The tools that we have created and utilize provide evidence of our involvement in the following areas: * Cancer Genomics * Data Repositories * iPhone & iPod Touch * microRNAs * Pathways * Protein Function * Text Analysis * Transcription Profiling
Proper citation: Computational Biology Center (RRID:SCR_002877) Copy
http://lab.rockefeller.edu/tuschl/
RNA is not only a carrier of genetic information, but also a catalyst and a guide for sequence-specific recognition and processing of other RNA molecules. This lab investigates the regulatory mechanisms of RNA interference, RNA-mediated translational control, and nuclear pre-mRNA splicing. Classical and combinatorial biochemical techniques are used to analyze the function of the RNA- and protein-components involved in those processes.
Proper citation: Tuschl Laboratory: RNA Molecular Biology (RRID:SCR_002866) Copy
A software package for the analysis of nucleotide polymorphism from aligned DNA sequence data. DnaSP can estimate several measures of DNA sequence variation within and between populations (in noncoding, synonymous or nonsynonymous sites, or in various sorts of codon positions), as well as linkage disequilibrium, recombination, gene flow and gene conversion parameters. DnaSP can also carry out several tests of neutrality: Hudson, Kreitman and Aguad (1987), Tajima (1989), McDonald and Kreitman (1991), Fu and Li (1993), and Fu (1997) tests. Additionally, DnaSP can estimate the confidence intervals of some test-statistics by the coalescent. The results of the analyses are displayed on tabular and graphic form.
Proper citation: DnaSP (RRID:SCR_003067) Copy
Digital atlas of gene expression patterns in developing and adult mouse. Several reference atlases are also available through this site. Expression patterns are determined by non-radioactive in situ hybridization on serial tissue sections. Sections are available from several developmental ages: E10.5, E14.5 (whole embryos), E15.5, P7 and P56 (brains only). To retrieve expression patterns, search by gene name, site of expression, GenBank accession number or sequence homology. For viewing expression patterns, GenePaint.org features virtual microscope tool that enables zooming into images down to cellular resolution.
Proper citation: GenePaint (RRID:SCR_003015) Copy
https://code.google.com/p/gutentag/
An interactive, user-editable genetic sequence database tool, targeted at molecular biology research groups that can be browsed using tags. The tool is Web 2.0-flavoured, allowing users to do more than just retrieve information. Its focus on user-editability is supported by the use of tags (metadata) associated with genetic sequences. Several methods of retrieving stored data are available including tag-clouds, BLAST and keyword searches. Also, sequence tags related to HGNC gene names, conserved domains (CDD) and GO terms can be automatically generated given sequence data. The tool is constructed using the high-level Python web framework, Django, with a SQLite3 backend.
Proper citation: Gutentag (RRID:SCR_003051) Copy
http://bibiserv.techfak.uni-bielefeld.de/dialign/
Tool for multiple sequence alignment using various sources of external information that is particularly useful to detect local homologies in sequences with low overall similarity. While standard alignment methods rely on comparing single residues and imposing gap penalties, DIALIGN constructs pairwise and multiple alignments by comparing entire segments of the sequences. No gap penalty is used. This approach can be used for both global and local alignment, but it is particularly successful in situations where sequences share only local homologies. Several versions of DIALIGN are available online at GOBICS, http://dialign.gobics.de/
Proper citation: DIALIGN (RRID:SCR_003041) Copy
http://iubio.bio.indiana.edu/webapps/SeWeR/
Sequence analysis using Web Resources (SeWeR) is an integrated, Dynamic HTML (DHTML) interface to commonly used bioinformatics services available on the World Wide Web. It is highly customizable, extendable, platform neutral, completely server-independent and can be hosted as a web page as well as being used as stand-alone software running within a web browser. It doesn''t require any server to host itself. The goal of SeWeR is to turn your web-browser into a powerful sequence-analysis tool. It is written entirely in JavaScript1.2. SeWeR can be downloaded and mirrored freely. The whole package is just around 300K. You can even run it from a floppy. SeWeR is not compatible with Netscape 6. SeWeR now generates graphics. Savvy is a plasmid drawing software that generates plasmid map in the revolutionary Scalable Vector Graphics format from W3C.
Proper citation: SeWeR - SEquence analysis using WEb Resources (RRID:SCR_004167) Copy
http://compbio.cs.sfu.ca/software-novelseq
Software pipeline to detect novel sequence insertions using high throughput paired-end whole genome sequencing data.
Proper citation: NovelSeq (RRID:SCR_003136) Copy
Database to catalog experimentally determined interactions between proteins combining information from a variety of sources to create a single, consistent set of protein-protein interactions that can be downloaded in a variety of formats. The data were curated, both, manually and also automatically using computational approaches that utilize the the knowledge about the protein-protein interaction networks extracted from the most reliable, core subset of the DIP data. Because the reliability of experimental evidence varies widely, methods of quality assessment have been developed and utilized to identify the most reliable subset of the interactions. This CORE set can be used as a reference when evaluating the reliability of high-throughput protein-protein interaction data sets, for development of prediction methods, as well as in the studies of the properties of protein interaction networks. Tools are available to analyze, visualize and integrate user's own experimental data with the information about protein-protein interactions available in the DIP database. The DIP database lists protein pairs that are known to interact with each other. By interact they mean that two amino acid chains were experimentally identified to bind to each other. The database lists such pairs to aid those studying a particular protein-protein interaction but also those investigating entire regulatory and signaling pathways as well as those studying the organization and complexity of the protein interaction network at the cellular level. Registration is required to gain access to most of the DIP features. Registration is free to the members of the academic community. Trial accounts for the commercial users are also available.
Proper citation: Database of Interacting Proteins (DIP) (RRID:SCR_003167) Copy
http://wiki.c2b2.columbia.edu/honiglab_public/index.php/Main_Page
Laboratory portal, including software, web-based tools, databases and data sets, related to their research that focuses on the development and application of biophysical and bioinformatics methods aimed at understanding the structural and energetic origins of protein-protein, protein-nucleic acid, and protein-membrane interactions. Their work includes fundamental theoretical research, the development of software tools, and applications to problems of biological importance. In this regard they maintain an active collaborative computational and experimental research program on the molecular basis of cell-cell adhesion. Other problems of current interest include protein structure prediction, the organization of protein sequence/structure space, the prediction of protein function based on protein structure, the structural origins of specificity in protein-DNA interactions, RNA function and, more generally, the electrostatic properties of biological macromolecules.
Proper citation: Honig Lab (RRID:SCR_003410) Copy
https://services.healthtech.dtu.dk/
Center for Biological Sequence Analysis of the Technical University of Denmark conducts basic research in the field of bioinformatics and systems biology and directs its research primarily towards topics related to the elucidation of the functional aspects of complex biological mechanisms. A large number of computational methods have been produced, which are offered to others via WWW servers. Several data sets are also available. The center also has experimental efforts in gene expression analysis using DNA chips and data generation in relation to the physical and structural properties of DNA. The on-line prediction services at CBS are available as interactive input forms. Most of the servers are also available as stand-alone software packages with the same functionality. In addition, for some servers, programmatic access is provided in the form of SOAP-based Web Services. The center also educates engineering students in biotechnology and systems biology and offers a wide range of courses in bioinformatics, systems biology, human health, microbiology and nutrigenomics.
Proper citation: DTU Center for Biological Sequence Analysis (RRID:SCR_003590) Copy
https://github.com/SciLifeLab/facs
Software for classification of Sequences using Bloom filters that can accurately and rapidly align sequences to a reference sequence.
Proper citation: FACS (RRID:SCR_000055) Copy
http://genome.crg.es/software/gfftools/GFF2PS.html
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software program for visualizing annotations of genomic sequences. The program has features such as the ability to create comprehensive plots, customizable parameters, and flexibility in file format.
Proper citation: Genome BioInformatics Research Lab - gff2ps (RRID:SCR_000462) Copy
http://trace.ddbj.nig.ac.jp/dor/index_e.html
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 6,2023. Archival database of functional genomics data generated by microarray and highly parallel new generation sequencers. Data are exchanged between ArrayExpress at EBI and DOR in common MAGE-TAB format. Supports MIAME and MINSEQE-compliant data submissions. DOR issues accession numbers, E-DORD-n to experiment and A-DORD-n to array design. DOR exchanges public data with the EBI ArrayExpress in common MAGE-TAB format. Note: At present, DOR does not accept submissions. DDBJ will announce launch of DOR when it is ready. (2013/01/31) The data can be kept private until your paper is published. You can set the hold date for a maximum of 1 year and can change it. Registered records are released according to the Data Release Policy.
Proper citation: DDBJ Omics Archive (RRID:SCR_000597) Copy
http://sourceforge.net/projects/fastuniq/
A software tool for removal of de novo duplicates in paired short DNA sequences.
Proper citation: FastUniq (RRID:SCR_000682) Copy
http://www.brown.edu/Research/Istrail_Lab/hapcompass.php
Software that utilizes a fast cycle basis algorithm for the accurate haplotype assembly of sequence data. It is able to create pairwise SNP phasings.
Proper citation: HapCompass (RRID:SCR_000942) Copy
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