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https://launchpad.net/asterias

A set of web-based applications for the analysis of genomic and proteomic data. Asterias combines Python with R and C/C++, using MPI for parallelization, and aspires to become a standard for high-performance, distributed, web-based bioinformatics and biostatistics applications.

Proper citation: Asterias (RRID:SCR_010936) Copy   

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http://chipster.csc.fi/

A user-friendly analysis software for high-throughput data.

Proper citation: Chipster (RRID:SCR_010939) Copy   

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http://plntfdb.bio.uni-potsdam.de

Public database arising from efforts to identify and catalogue all plant genes involved in transcriptional control.Integrative plant transcription factor database that provides web interface to access large sets of transcription factors of several plant species, currently encompassing Arabidopsis thaliana (thale cress), Populus trichocarpa (poplar), Oryza sativa (rice), Chlamydomonas reinhardtii and Ostreococcus tauri. Provides access point to its daughter databases of species-centered representation of transcription factors (OstreoTFDB, ChlamyTFDB, ArabTFDB, PoplarTFDB and RiceTFDB). Information including protein sequences, coding regions, genomic sequences, expressed sequence tags, domain architecture and scientific literature is provided for each family.

Proper citation: PlnTFDB (RRID:SCR_010899) Copy   

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http://methmarker.mpi-inf.mpg.de/

Tool that facilitates the design and optimization of gene-specific DNA methylation assays. Beyond its use as an epigenetic primer-design tool, it provides extensive support for epigenetic biomarker optimization. Download MethMarker or start it directly from within your web browser.

Proper citation: MethMarker (RRID:SCR_010908) Copy   

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http://sissrs.rajajothi.com/

Anl algorithm for precise identification of binding sites from short reads generated from ChIP-Seq experiments.

Proper citation: SISSRs (RRID:SCR_010866) Copy   

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http://code.google.com/p/zinba/

Software to identify genomic regions enriched in a variety of ChIP-seq and related next-generation sequencing experiments (DNA-seq), calling both broad and narrow modes of enrichment across a range of signal-to-noise ratios. ZINBA models and accounts for factors that co-vary with background or experimental signal, such as G/C content, and identifies enrichment in genomes with complex local copy number variations. ZINBA provides a single unified framework for analyzing DNA-seq experiments in challenging genomic contexts.

Proper citation: ZINBA (RRID:SCR_010868) Copy   

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http://aroma-project.org/

An R package for analyzing large Affymetrix data sets.

Proper citation: Aroma.affymetrix (RRID:SCR_010919) Copy   

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http://kmersvm.beerlab.org/

A webserver built on the Galaxy framework that enables the mining of sequence data for transcription factor binding sites. This tool suite was designed to aid in analysis of next-generation sequencing (NGS) data that uses a support vector machine (SVM) with kmer sequence features to identify predictive combinations of short transcription factor binding sites which determine the tissue specificity of the original NGS assay. While you may use datasets already available from Galaxy, you can upload your data using the ''Get Data'' Tool. The tool can upload data from a variety of locations.

Proper citation: kmer-SVM (RRID:SCR_010882) Copy   

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http://pilgrm.princeton.edu

PILGRM (the platform for interactive learning by genomics results mining) puts advanced supervised analysis techniques applied to enormous gene expression compendia into the hands of bench biologists. This flexible system empowers its users to answer diverse biological questions that are often outside of the scope of common databases in a data-driven manner. This capability allows domain experts to quickly and easily generate hypotheses about biological processes, tissues or diseases of interest. Specifically PILGRM helps biologists generate these hypotheses by analyzing the expression levels of known relevant genes in large compendia of microarray data. PILGRM is for the biologist with a set of proteins relevant to a disease, biological function or tissue of interest who wants to find additional players in that process. It uses a data driven method that provides added value for literature search results by mining compendia of publicly available gene expression datasets using lists of relevant and irrelevant genes (standards). PILGRM produces publication quality PDFs usable as supplementary material to describe the computational approach, standards and datasets. Each PILGRM analysis starts with an important biological question (e.g. What genes are relevant for breast cancer but not mammary tissue in general?). For PILGRM to discover relevant genes, it needs examples of both genes that you would (positive) and would not (negative) find interesting. Lists of these genes are what we call standards and in PILGRM you can build your own standards or you can use standards from common sources that we pre-load for your convenience. PILGRM lets you build your own literature-documented standards so that processes, disease, and tissues that are not well covered in databases of tissue expression, disease, or function can still be used for an analysis.

Proper citation: PILGRM (RRID:SCR_004749) Copy   

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http://swift.cmbi.ru.nl/gv/hssp/

HSSP (homology-derived structures of proteins) is a derived database merging structural (2-D and 3-D) and sequence information (1-D). For each protein of known 3D structure from the Protein Data Bank, the database has a file with all sequence homologues, properly aligned to the PDB protein. Homologues are very likely to have the same 3D structure as the PDB protein to which they have been aligned. As a result, the database is not only a database of sequence aligned sequence families, but it is also a database of implied secondary and tertiary structures. Likely secondary structure are carried over from the PDB protein to each homologous protein. Tertiary structure models can be built by fitting the sequence of the homologue as aligned into the 3D template of the protein of known structure. Special software is needed to construct 3D models by homology, such WHATIF by Gert Vriend or MaxSprout by Liisa Holm and Chris Sander. The command rsync can be used to obtain a local copy of the HSSP. We appreciate receiving an Email from people who do so, but there are no strings attached. Everybody can freely download the files, academia and industry alike. If your institute''s firewall doesn''t allow you to use the (preferred) rsync way of obtaining HSSP files, feel free to work with FTP. The files are in that case available from: ftp://ftp.cmbi.ru.nl//pub/molbio/data/hssp/

Proper citation: HSSP (RRID:SCR_004953) Copy   

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http://sms.cbi.cnptia.embrapa.br/SMS/STINGm/SMSReport/

Sting Report is a database of amino acid sequences, structures, functions, and parameters. It allows users to easily extract from the Blue Star Sting Database detailed but focused information about an individual amino acid, which belongs to a structure described in a PDB file. The extracted information is presented as a series of GIF images and a table, which are generated by Blue Star Sting modules and contain values of up to 125 sequence/structure/function descriptors/parameters. The HTML page resulting from a query on Sting Report, containing the GIF images and the table, is printable, and can also be composed and visualized at a computer platform with elementary configuration.

Proper citation: STING Report (RRID:SCR_005121) Copy   

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http://www.ihop-net.org/UniPub/iHOP/

Information system that provides a network of concurring genes and proteins extends through the scientific literature touching on phenotypes, pathologies and gene function. It provides this network as a natural way of accessing millions of PubMed abstracts. By using genes and proteins as hyperlinks between sentences and abstracts, the information in PubMed can be converted into one navigable resource, bringing all advantages of the internet to scientific literature research. Moreover, this literature network can be superimposed on experimental interaction data (e.g., yeast-two hybrid data from Drosophila melanogaster and Caenorhabditis elegans) to make possible a simultaneous analysis of new and existing knowledge. The network contains half a million sentences and 30,000 different genes from humans, mice, D. melanogaster, C. elegans, zebrafish, Arabidopsis thaliana, yeast and Escherichia coli.

Proper citation: Information Hyperlinked Over Proteins (RRID:SCR_004829) Copy   

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http://spot.cgsmd.isi.edu

A web-based tool for using biological databases to prioritize single nucleotide polymorphisms (SNPs) after a genome-wide association study (GWAS). The site allows users to upload a list of SNPs and GWAS P-values and returns a prioritized list of SNPs using the GIN method. Users can specify candidate genes or genomic regions with custom levels of prioritization. The results can be downloaded or viewed in the browser where users can interactively explore the details of each SNP, including graphical representations of the genomic information network (GIN) method. For investigators interested in incorporating biological databases into a post-GWAS SNP selection strategy, the SPOT web tool is an easily implemented and flexible solution.

Proper citation: SPOT - Biological prioritization after a SNP association study (RRID:SCR_005193) Copy   

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http://metagenomics.anl.gov/

An automated analysis platform for metagenomes providing quantitative insights into microbial populations based on sequence data. The server primarily provides upload, quality control, automated annotation and analysis for prokaryotic metagenomic shotgun samples.

Proper citation: MG-RAST (RRID:SCR_004814) Copy   

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http://www.gomapman.org/

An open web-accessible resource for gene functional annotations in the plant sciences to facilitate improvement, consolidation and visualization of gene annotations across several plant species. It is based on the MapMan ontology, organized in the form of a hierarchical tree of biological concepts, which describe gene functions. Currently, genes of the model species Arabidopsis, potato, tomato, rice, and tobacco are included. The main features are (i) dynamic and interactive gene product annotation through various curation options; (ii) consolidation of gene annotations for different plant species through the integration of orthologue group information; (iii) traceability of gene ontology changes and annotations; (iv) integration of external knowledge about genes from different public resources; and (v) providing gathered information to high-throughput analysis tools via dynamically generated export files. All of the GoMapMan functionalities are openly available, with the restriction on the curation functions, which require prior registration to ensure traceability of the implemented changes.

Proper citation: GoMapMan (RRID:SCR_005060) Copy   

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http://www.umd.be/HSF3/

Software tool to help study pre-mRNA splicing and to better understand intronic and exonic mutations leading to splicing defects. To calculate the consensus values of potential splice sites and search for branch points, new algorithms were developed. Furthermore, they have integrated all available matrices to identify exonic and intronic motifs, as well as new matrices to identify hnRNP A1, Tra2-? and 9G8.

Proper citation: Human Splicing Finder (RRID:SCR_005181) Copy   

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http://ahdb.ee.ncku.edu.tw/

Database of apo and holo structure pairs of proteins before and after binding. Various protein functions have been shown directly associated with conformational transitions triggered by binding other molecules. Tertiary structures determined in the unbound and bound state are usually named apo and holo structures, respectively. AH-DB is the largest database of apo-holo structure pairs and provides a sophisticated interface to search and view the collected data. It contains 746314 apo-holo pairs of 3638 proteins from 702 organisms.

Proper citation: Apo and Holo structures DataBase (RRID:SCR_004800) Copy   

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http://www.ncbi.nlm.nih.gov/bioproject

Database of biological data related to a single initiative, originating from a single organization or from a consortium. A BioProject record provides users a single place to find links to the diverse data types generated for that project. It is a searchable collection of complete and incomplete (in-progress) large-scale sequencing, assembly, annotation, and mapping projects for cellular organisms. Submissions are supported by a web-based Submission Portal. The database facilitates organization and classification of project data submitted to NCBI, EBI and DDBJ databases that captures descriptive information about research projects that result in high volume submissions to archival databases, ties together related data across multiple archives and serves as a central portal by which to inform users of data availability. BioProject records link to corresponding data stored in archival repositories. The BioProject resource is a redesigned, expanded, replacement of the NCBI Genome Project resource. The redesign adds tracking of several data elements including more precise information about a project''''s scope, material, and objectives. Genome Project identifiers are retained in the BioProject as the ID value for a record, and an Accession number has been added. Database content is exchanged with other members of the International Nucleotide Sequence Database Collaboration (INSDC). BioProject is accessible via FTP.

Proper citation: NCBI BioProject (RRID:SCR_004801) Copy   

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http://ilyinlab.org/StSNP/

A web server for mapping and modeling nsSNPs on protein structures with linkage to metabolic pathways.

Proper citation: StSNP (RRID:SCR_005417) Copy   

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http://edwards.sdsu.edu/cgi-bin/prinseq/prinseq.cgi

A publicly available tool that is able to filter, reformat and trim your genomic and metagenomic sequence data and provide you summary statistics for your sequence data. The interactive web interface facilitates visualizations of the results and export functionality for subsequent data processing. The standalone lite version is written in Perl and does not require any non-core Perl modules. The lite version is primarily designed for data preprocessing and does not generate summary statistics in graphical form., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PRINSEQ (RRID:SCR_005454) Copy   

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