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http://www.genoscope.cns.fr/spip/spip.php?lang=en

French national sequencing center with the following resources: * Sequencing ** Genoscope Projects * Environmental genomics ** Microbial diversity in wastewater ** Metabolic genomics * Bioinformatics ** Atelier for comparative genomics ** Computational Systems Biology ** Servers resources *** GGB for Generic Genome Browser: graphic interface for various databases (sequence, annotation, syntenies...) for a given organism. *** MaGe for Magnifying Microbial Genomes: annotation system for microbial genomes.

Proper citation: Genoscope (RRID:SCR_002172) Copy   

•   Source: SciCrunch Registry

http://genomejack.net/

A genome browser specialized in next-generation sequencing data.

Proper citation: GenomeJack (RRID:SCR_012026) Copy   

•   Source: SciCrunch Registry

http://gmod.org/wiki/Flash_GViewer

Flash GViewer is a customizable Flash movie that can be easily inserted into a web page to display each chromosome in a genome along with the locations of individual features on the chromosomes. It is intended to provide an overview of the genomic locations of a specific set of features - eg. genes and QTLs associated with a specific phenotype, etc. rather than as a way to view all features on the genome. The features can hyperlink out to a detail page to enable to GViewer to be used as a navigation tool. In addition the bands on the chromosomes can link to defineable URL and new region selection sliders can be used to select a specific chromosome region and then link out to a genome browser for higher resolution information. Genome maps for Rat, Mouse, Human and C. elegans are provided but other genome maps can be easily created. Annotation data can be provided as static text files or produced as XML via server scripts. This tool is not GO-specific, but was built for the purpose of viewing GO annotation data. Platform: Online tool

Proper citation: Flash Gviewer (RRID:SCR_012870) Copy   

•   Source: SciCrunch Registry

http://diprogb.fli-leibniz.de/

Genome browser that encodes the genome sequence by physico-chemical dinucleotide properties such as stacking energy, melting temperature or twist angle. Analyses can be performed for the + and ?, as well as for the double strand.

Proper citation: DiProGB (RRID:SCR_005651) Copy   

•   Source: SciCrunch Registry

http://www.bioinformatics.babraham.ac.uk/projects/bismark/

Software tool to map bisulfite converted sequence reads and determine cytosine methylation states. Flexible aligner and methylation caller for Bisulfite-Seq applications. Used to map bisulfite treated sequencing reads to genome of interest and perform methylation calls in single step.

Proper citation: Bismark (RRID:SCR_005604) Copy   

•   Source: SciCrunch Registry

http://staden.sourceforge.net/

A fully developed set of DNA sequence assembly (Gap4 and Gap5), editing and analysis tools (Spin) for Unix, Linux, MacOSX and MS Windows.

Proper citation: Staden Package (RRID:SCR_005629) Copy   

•   Source: SciCrunch Registry

http://genomefoundation.org/index.php/Main_Page

The Genome Foundation (AKA Genome Research Foundation) is a fully government accredited and registered non-profit research foundation. GRF aims to provide genome philosophy, science, and technology. GRF is a nonprofit publisher, and research and advocacy organization to promote completely free publication of knowledge with minimum restriction. Our core objectives are to: * Provide ways to overcome unnecessary barriers to immediate availability, access, and use of research * Pursue a publishing strategy that optimizes the openness, quality, and integrity of the publication process * Develop innovative approaches to the assessment, organization, and reuse of ideas and data Genome Foundation Research * Personalized Medicine * Personal Genomics * AngioGenesis drug * Bioinformatics * RNA expression * Protein structure * Human Genome Rights Projects at Genome Foundation * The Human Genome Rights * Human Genome Rights Petition * Free Personal Genome Sequencing Project * Free Personal Genome Sequencing Petition * Tiger Genome Initiative: Amur Tiger and big cat genomes * Whale Genome Project

Proper citation: Genome Research Foundation (RRID:SCR_006056) Copy   

•   Source: SciCrunch Registry

http://pathogenseq.lshtm.ac.uk/estmoi

A per-based software to estimate multiplicity of infection (MOI) in parasite genomic sequence data. It is primarily developed to address the limitations of current laboratory (PCR) based estimates of multiplicity using high throughput sequence data. It requires a BAM (alignment output of short reads to the reference genome), VCF (a file with information on variant calls) and FASTA (reference genome) files. # Short reads are aligned to a reference genome using BWA, BOWTIE, SMALT or other short read aligners to generate a BAM file. # Single Nucleotide Polymorphisms (SNPs) are then identified using SAMTools/BCFtools and stored in the VCF format. # The reference FASTA file is expected to be indexed using ''samtools faidx'' to generate a *.fai file. estMOI generates files containing MOI estimates for each SNP combinations (file with name *.log) and a summary for all chromosomes (file with name *.txt).

Proper citation: estMOI (RRID:SCR_006192) Copy   

•   Source: SciCrunch Registry

https://www.thermofisher.com/order/catalog/product/00-0210

Scanner for microarray analysis to scan next-generation higher-density arrays, including SNP arrays, tiling arrays for transcription and all-exon arrays for whole-genome analysis.

Proper citation: GeneChip™ Scanner 3000 7G (RRID:SCR_016522) Copy   

•   Source: SciCrunch Registry

https://github.com/friend1ws/EBCall

A software package for somatic mutation detection (including InDels). EBCall uses not only paired tumor/normal sequence data of a target sample, but also multiple non-paired normal reference samples for evaluating distribution of sequencing errors, which leads to an accurate mutaiton detection even in case of low sequencing depths and low allele frequencies.

Proper citation: EBCall (RRID:SCR_006791) Copy   

•   Source: SciCrunch Registry

http://bioviz.org/igb/

An easy-to-use, highly customizable genome browser you can use to visualize and explore genomic data and annotations, including RNA-Seq, ChIP-Seq, tiling array data, and more.

Proper citation: IGB (RRID:SCR_011792) Copy   

•   Source: SciCrunch Registry

http://promoter.bx.psu.edu/hi-c/

Genome Browser for study of 3D genome organization and gene regulation and data visualization. Used to visualizing chromatin interaction data, browse other omics data such as ChIP-Seq or RNA-Seq for same genomic region, and gain complete view of both regulatory landscape and 3D genome structure for any given gene., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: 3D Genome (RRID:SCR_017525) Copy   

•   Source: SciCrunch Registry

http://svdetect.sourceforge.net/Site/Home.html

Software application for the isolation and the type prediction of intra- and inter-chromosomal rearrangements from paired-end/mate-pair sequencing data provided by the high-throughput sequencing technologies. This tool aims to identify structural variations with both clustering and sliding-window strategies, and helping in their visualization at the genome scale. It is compatible with SOLiD and Illumina (>=1.3) reads.

Proper citation: SVDetect (RRID:SCR_010812) Copy   

•   Source: SciCrunch Registry

http://www-bio3d-igbmc.u-strasbg.fr/ICDS/

Database of interrupted coding sequences detected by a similarity-based approach in complete prokaryotic genomes. The definition of each interrupted gene is provided as well as the ICDS genomic localization with the surrounding sequence. To facilitate the experimental characterization of ICDS, optimized primers are proposed for re-sequencing purposes. The database is accessible by BLAST search or by genome. 118 Genomes are available in the database.

Proper citation: Interrupted CoDing Sequence Database (RRID:SCR_002949) Copy   

•   Source: SciCrunch Registry

http://mirnamap.mbc.nctu.edu.tw

A database of experimentally verified microRNAs and miRNA target genes in human, mouse, rat, and other metazoan genomes. In addition to known miRNA targets, three computational tools previously developed, such as miRanda, RNAhybrid and TargetScan, were applied for identifying miRNA targets in 3'-UTR of genes. In order to reduce the false positive prediction of miRNA targets, several criteria are supported for filtering the putative miRNA targets. Furthermore, miRNA expression profiles can provide valuable clues for investigating the properties of miRNAs, such tissue specificity and differential expression in cancer/normal cell. Therefore, we performed the Q-PCR experiments for monitoring the expression profiles of 224 human miRNAs in eighteen major normal tissues in human. The cross-reference between the miRNA expression profiles and the expression profiles of its target genes can provide effective viewpoint to understand the regulatory functions of the miRNA.

Proper citation: miRNAMap (RRID:SCR_003156) Copy   

•   Source: SciCrunch Registry

http://www.mitomap.org/

Database of polymorphisms and mutations of the human mitochondrial DNA. It reports published and unpublished data on human mitochondrial DNA variation. All data is curated by hand. If you would like to submit published articles to be included in mitomap, please send them the citation and a pdf.

Proper citation: MITOMAP - A human mitochondrial genome database (RRID:SCR_002996) Copy   

•   Source: SciCrunch Registry

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

Collection of curated, non-redundant genomic DNA, transcript RNA, and protein sequences produced by NCBI. Provides a reference for genome annotation, gene identification and characterization, mutation and polymorphism analysis, expression studies, and comparative analyses. Accessed through the Nucleotide and Protein databases.

Proper citation: RefSeq (RRID:SCR_003496) Copy   

•   Source: SciCrunch Registry

http://genomequebec.mcgill.ca/PReMod

Database that describes more than 100,000 computational predicted transcriptional regulatory modules within the human genome. These modules represent the regulatory potential for 229 transcription factors families and are the first genome-wide / transcription factor-wide collection of predicted regulatory modules for the human genome. The algorithm used involves two steps: (i) Identification and scoring of putative transcription factor binding sites using 481 TRANSFAC 7.2 position weight matrices (PWMs) for vertebrate transcription factors. To this end, each non-coding position of the human genome was evaluated for its similarity to each PWM using a log-likelihood ratio score with a local GC-parameterized third-order Markov background model. Corresponding orthologous positions in mouse and rat genomes were evaluated similarly and a weighted average of the human, mouse, and rat log-likelihood scores at aligned positions (based on a Multiz (Blanchette et al. 2004) genome-wide alignment of these three species) was used to define the matrix score for each genomic position and each PWM. (ii) Detection of clustered putative binding sites. To assign a module score to a given region, the five transcription factors with the highest total scoring hits are identified, and a p-value is assigned to the total score observed of the top 1, 2, 3, 4, or 5 factors. The p-value computation takes into consideration the number of factors involved (1 to 5), their total binding site scores, and the length and GC content of the region under evaluation. Users can retrieve all information for a given region, a given PWM, a given gene and so on. Several options are given for textual output or visualization of the data.

Proper citation: PReMod (RRID:SCR_003403) Copy   

•   Source: SciCrunch Registry

http://www.flytf.org/

A database of genomic and protein data for Drosophila site-specific transcription factors.

Proper citation: FlyTF.org (RRID:SCR_004123) Copy   

•   Source: SciCrunch Registry

http://bioinfo.mbi.ucla.edu/ASAP/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on 8/12/13. Database to access and mine alternative splicing information coming from genomics and proteomics based on genome-wide analyses of alternative splicing in human (30 793 alternative splice relationships found) from detailed alignment of expressed sequences onto the genomic sequence. ASAP provides precise gene exon-intron structure, alternative splicing, tissue specificity of alternative splice forms, and protein isoform sequences resulting from alternative splicing. They developed an automated method for discovering human tissue-specific regulation of alternative splicing through a genome-wide analysis of expressed sequence tags (ESTs), which involves classifying human EST libraries according to tissue categories and Bayesian statistical analysis. They use the UniGene clusters of human Expressed Sequence Tags (ESTs) to identify splices. The UniGene EST's are clustered so that a single cluster roughly corresponds to a gene (or at least a part of a gene). A single EST represents a portion of a processed (already spliced) mRNA. A given cluster contains many ESTs, each representing an outcome of a series of splicing events. The ESTs in UniGene contain the different mRNA isoforms transcribed from an alternatively spliced gene. They are not predicting alternative splicing, but locating it based on EST analysis. The discovered splices are further analyzed to determine alternative splicing events. They have identified 6201 alternative splice relationships in human genes, through a genome-wide analysis of expressed sequence tags (ESTs). Starting with 2.1 million human mRNA and EST sequences, they mapped expressed sequences onto the draft human genome sequence and only accepted splices that obeyed the standard splice site consensus. After constructing a tissue list of 46 human tissues with 2 million human ESTs, they generated a database of novel human alternative splices that is four times larger than our previous report, and used Bayesian statistics to compare the relative abundance of every pair of alternative splices in these tissues. Using several statistical criteria for tissue specificity, they have identified 667 tissue-specific alternative splicing relationships and analyzed their distribution in human tissues. They have validated our results by comparison with independent studies. This genome-wide analysis of tissue specificity of alternative splicing will provide a useful resource to study the tissue-specific functions of transcripts and the association of tissue-specific variants with human diseases.

Proper citation: ASAP: the Alternative Splicing Annotation Project (RRID:SCR_003415) Copy   

•   Source: SciCrunch Registry