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http://merops.sanger.ac.uk/

An information resource for peptidases (also termed proteases, proteinases and proteolytic enzymes) and the proteins that inhibit them. The MEROPS database uses an hierarchical, structure-based classification of the peptidases. In this, each peptidase is assigned to a Family on the basis of statistically significant similarities in amino acid sequence, and families that are thought to be homologous are grouped together in a Clan. There is a Summary page for each family and clan, and these have indexes. Each of the Summary pages offers links to supplementary pages. About 3000 individual peptidases and inhibitors are included in the database, and there is a Summary page describing each one. You can navigate to this by any of several routes. There are indexes of Name, MEROPS Identifier and source Organism on the menu bar. Each Summary page describes the classification and nomenclature of the peptidase or inhibitor, and provides links to supplementary pages showing sequence identifiers, the structure if known, literature references and more.

Proper citation: MEROPS (RRID:SCR_007777) Copy   

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http://locate.imb.uq.edu.au/

LOCATE is a curated database that houses data describing the membrane organization and subcellular localization of proteins from the RIKEN FANTOM4 mouse and human protein sequence set. The membrane organization is predicted by the high-throughput, computational pipeline MemO. The subcellular locations were determined by a high-throughput, immunofluorescence-based assay and by manually reviewing peer-reviewed publications.

Proper citation: LOCATE: subcellular localization database (RRID:SCR_007763) Copy   

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http://biobases.ibch.poznan.pl/ncRNA/

It is intended to provide information on the sequences and functions of transcripts which do not code for proteins, but perform regulatory roles in the cell. Currently, the database includes over 30,000 individual sequences from 99 species of Bacteria, Archaea and Eukaryota. The primary source of sequences included in the database was the GenBank. Additional annotation information for mouse and human ncRNAs was derived from FANTOM3 database and H-inviational Integrated Database of Annotated Human Genes version 3.4, respectively. Genome mapping information was derived from tha data available at the UCSC Genome Browser site. The sequences and annotations of small cytoplasmic RNAs from bacteria, for which annotation is lacking in the genome sequences, were derived from the Rfam database. The microRNAs or snoRNAs which were available in previous editions, as well as other housekeeping (infrastructural) RNAs (e.g. rRNA, tRNA, snRNA, SRP RNA) are not included in our database to avoid redundancy with more specialized databases which emerged in recent years.

Proper citation: Noncoding RNA database (RRID:SCR_007815) Copy   

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http://www.cmbi.ru.nl/phylopat

A database of phylogenetic patterns of evolution between 46 different species. PhyloPat uses the latest release of EnsMart (release 52), and their one-to-one, one-to-many and many-to-many orthologies. First, we stored all of the Ensembl IDs within the 46 species, and the orthologies between them. Second, we determined the evolutionary order of the studied species using the NCBI Taxonomy database. The phylogenetic tree of these species can be viewed here. Third, we used this phylogenetic tree as a starting point for building our phylogenetic lineages. For each gene in the first species (S. cerevisiae), we looked for orthologs in the other species. All orthologs were added to the phylogenetic lineage, and in the next round were checked for orthologs themselves, until no more orthologies were found for any of the genes. This process was repeated for all genes in all species that were not connected to any phylogenetic lineage yet. The complete phylogenetic lineage determination generated 329,998 phylogenetic lineages, consisting of 973,821 genes. These lineages can be queried here by phylogenetic patterns, MySQL regular expressions or simply a list of Ensembl/EMBL/EntrezGene/HGNC IDs. Output can be given in HTML, Excel or plain text format.

Proper citation: PhyloPat (RRID:SCR_007851) Copy   

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http://phylomedb.bioinfo.cipf.es

Database for phylomes, that is, complete collections of phylogenetic trees for all proteins encoded in a given genome. It aims at providing a repository of high-quality phylogenies and alignments for proteins encoded in model species. To derive a phylome, each protein encoded in a given genome is used as a seed to retrieve its homologs in other complete genomes. These sequences are aligned and processed to derive reliable phylogenies using several phylogenetic methods. Besides providing the evolutionary history of the gene families, phylomeDB includes phylogeny based predictions of orthology and paralogy relationships., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PhylomeDB (RRID:SCR_007850) Copy   

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http://www.partigenedb.org/

A publicly available database resource containing the assembled partial genomes for ~700 eukaryotic organisms. Partial genomes are generated from expressed sequence tag datasets containing more than 1000 sequences. PartiGeneDB allows users to view sets of genes and identify genes of interest in organisms for which a full genome is not currently available. PartiGeneDB is automatically updated to include new organism datasets as they are generated. PartiGeneDB provides four portals of entry into the database. It is hosted and supported by the Hospital for Sick Children, Toronto. In addition to providing a comprehensive resource facilitating comparative analyses, PartiGeneDB allows researchers to access the partial genomes of organisms that may not be available elsewhere. However, we recommend and encourage users interested in exploring datasets from a single organism in more depth, that you visit the specific web sites associated with the sequencing effort associated with that organism .

Proper citation: PartiGeneDB (RRID:SCR_007848) Copy   

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http://bioafrica.mrc.ac.za/rnavirusdb/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 19, 2016. It is a database and web application describing the genome organization and providing analytical tools for the 938 known species of RNA virus. It can identify submitted nucleotide sequences, can place them into multiple whole-genome alignments (in species where more than one isolate has been fully sequenced) and contains translated genome sequences for all species. It has been created for two main purposes: to facilitate the comparative analysis of RNA viruses and to become a hub for other, more specialised virus Web sites.

Proper citation: RNA Virus Database (RRID:SCR_007899) Copy   

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http://statgen.ncsu.edu/asg/

Alternative splicing essentially increases the diversity of the transcriptome and has important implications for physiology, development and the genesis of diseases. This resource uses a different approach to investigate alternative splicing (instead of the conventional case-by case fashion) and integrates all transcripts derived from a gene into a single splicing graph. ASG is a database of splicing graphs for human genes, using transcript information from various major sources (Ensembl, RefSeq, STACK, TIGR and UniGene). Each transcript corresponds to a path in the graph, and alternative splicing is displayed by bifurcations. This representation preserves the relationships between different splicing variants and allows us to investigate systematically all possible putative transcripts. Web interface allows users to display the splicing graphs, to interactively assemble transcripts and to access their sequences as well as neighboring genomic regions. ASG also provide for each gene, an exhaustive pre-computed catalog of putative transcriptsin total more than 1.2 million sequences. It has found that ~65 of the investigated genes show evidence for alternative splicing, and in 5 of the cases, a single gene might produce over 100 transcripts.

Proper citation: Alternate splicing gallery (RRID:SCR_008129) Copy   

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http://www.mgc.ac.cn/VFs/

An integrated and comprehensive database of virulence factors for bacterial pathogens (also including Chlamydia and Mycoplasma). VFDB is a platform for further study of comparative pathogenomics. Major features include tabular comparison of pathogenomic composition in terms of virulence, multiple alignments and statistic analysis of homologous virulence genes, and graphical comparison of pathogenomic organization of VFs. Category: Genomics Databases (non-vertebrate) Subcategory: Prokaryotic genome databases

Proper citation: VFDB - Virulence Factors of Bacterial Pathogens (RRID:SCR_007969) Copy   

•   Source: SciCrunch Registry

http://tdrtargets.org/

This database functions both as a website where researchers can look for information on their targets of interest; and as a tool for prioritization of targets in whole genomes. Using the database as a tool, researchers can quickly prioritize a genome of interest by performing any number of individual queries on a species of interest, then assigning numerical weights to each query (in the history page) to finally obtain a ranked list of genes by combining the weighted queries. This site is part of a WHO/TDR project seeking to exploit the availability of diverse datasets to facilitate the identification and prioritization of drug targets in pathogens causing neglected diseases.

Proper citation: TDR Targets Database (RRID:SCR_007963) Copy   

•   Source: SciCrunch Registry

http://hannonlab.cshl.edu/fastx_toolkit/

Software tool as collection of command line tools for Short-Reads FASTA/FASTQ files preprocessing.

Proper citation: FASTX-Toolkit (RRID:SCR_005534) Copy   

•   Source: SciCrunch Registry

http://idash.ucsd.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 6, 2023. National Center for Biomedical Computing (NCBC) that develops new algorithms, opensource tools, computational infrastructure, and services for biomedical and behavioral researchers nationwide to promote the secure sharing and consuming of biomedical and behavioral resources (software, data, and computing systems) with iDASH collaborators. The center addresses fundamental challenges to research progress by providing a secure, privacypreserving environment in which researchers can analyze genomic, transcriptomic, clinical, behavioral, and social data relevant to health. Three driving biological projects in iDASH (Molecular Phenotyping of Kawasaki Disease, Post-Marketing Surveillance of Hematologic Medications, and Individualized Intervention to Enhance Physical Activity) span the molecular-individualpopulation spectrum, and they will motivate, inform, and support tool development. iDASH will collaborate with other NCBCs and will disseminate tools via annual workshops, presentations at major conferences, and scientific publications.

Proper citation: iDASH (RRID:SCR_003524) Copy   

•   Source: SciCrunch Registry

https://github.com/gt1/biobambam

Software tools for read pair collation based algorithms on BAM files including * bamcollate2: reads BAM and writes BAM reordered such that alignment or collated by query name * bammarkduplicates: reads BAM and writes BAM with duplicate alignments marked using the BAM flags field * bammaskflags: reads BAM and writes BAM while masking (removing) bits from the flags column * bamrecompress: reads BAM and writes BAM with a defined compression setting. This tool is capable of multi-threading. * bamsort: reads BAM and writes BAM resorted by coordinates or query name * bamtofastq: reads BAM and writes FastQ; output can be collated or uncollated by query name

Proper citation: biobambam (RRID:SCR_003308) Copy   

•   Source: SciCrunch Registry

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

A software application for viewing and processing DNA sequencing chromatograms (trace files) that makes it easy to quickly generate high-quality finished sequences from a large number of trace files. SeqTrace can automatically identify, align, and compute consensus sequences from matching forward and reverse traces, filter low-quality base calls, and perform end trimming of finished sequences. The finished DNA sequences can then be exported to common sequence file formats, such as FASTA. SeqTrace also includes a full-featured trace file viewer and editor. You can view your sequencing chromatograms at a variety of scales and zoom levels, simultaneously view matching forward and reverse traces, edit the called bases, and export individual DNA sequences as well as forward/reverse alignments. SeqTrace supports popular trace file formats, including ABIF, SCF, and ZTR.

Proper citation: SeqTrace (RRID:SCR_005580) Copy   

•   Source: SciCrunch Registry

http://phenoscape.org/

Project to create a scalable infrastructure that enables linking phenotypes across different fields of biology by the semantic similarity of their descriptions.

Proper citation: Phenoscape (RRID:SCR_003799) Copy   

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http://mgc.nci.nih.gov/

NIH initiative project to provide full-length open reading frame (FL-ORF) clones for human, mouse, and rat genes, cow. MGC cDNA clones were obtained by screening of cDNA libraries, by transcript-specific RT-PCR cloning, and by DNA synthesis of cDNA inserts. All MGC sequences are deposited in GenBank and clones can be purchased from distributors of IMAGE consortium. With conclusion of MGC project in March 2009, GenBank records of MGC sequences will be frozen, without further updates. Since definition of what constitutes full-length coding region for some of genes and transcripts for which they have MGC clones will likely change in future, users planning to order MGC clones will need to monitor for these changes. Users can make use of genome browsers and gene-specific databases, such as the UCSC Genome browser, NCBI's Map Viewer, and Entrez Gene, to view relevant regions of genome (browsers) or gene-related information (Entrez Gene).

Proper citation: Mammalian Gene Collection (RRID:SCR_007024) Copy   

•   Source: SciCrunch Registry

https://github.com/najoshi/sickle

Software tool for windowed adaptive trimming for fastq files using quality. Supports quality values like Illumina, Solexa, and Sanger. Takes the quality values and slides a window across them whose length is 0.1 times the length of the read.

Proper citation: Sickle (RRID:SCR_006800) Copy   

•   Source: SciCrunch Registry

http://cellprofiler.org

Software tool to enable biologists without training in computer vision or programming to quantitatively measure phenotypes from thousands of images automatically. It counts cells and also measures the size, shape, intensity and texture of every cell (and every labeled subcellular compartment) in every image. It was designed for high throughput screening but can perform automated image analysis for images from time-lapse movies and low-throughput experiments. CellProfiler has an increasing number of algorithms to identify and measure properties of neuronal cell types.

Proper citation: CellProfiler Image Analysis Software (RRID:SCR_007358) Copy   

•   Source: SciCrunch Registry

http://www.biojava.org

Project dedicated to providing Java framework for processing biological data. It provides analytical and statistical routines, parsers for common file formats and allows the manipulation of sequences and 3D structures. The goal of the biojava project is to facilitate rapid application development for bioinformatics. Sponsor: BioJava is not formally funded by any grants. Through the OBF they have received sponsorship from Sun Microsystems, Apple Computers and NESCent. The initial development of the phylogenetics module was undertaken as a Google Summer of Code 2007 project in collaboration with NESCent.

Proper citation: BioJava Project (RRID:SCR_007180) Copy   

•   Source: SciCrunch Registry

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

A native Java-based imaging processing environment similar to the ITK/VTK paradigm. Initially developed as an extension to MIPAV (CIT, NIH, Bethesda, MD), the JIST processing infrastructure provides automated GUI generation for application plug-ins, graphical layout tools, and command line interfaces. This repository maintains the current multi-institutional JIST development tree and is recommended for public use and extension. JIST was originally developed at IACL and MedIC (Johns Hopkins University) and is now also supported by MASI (Vanderbilt University).

Proper citation: JIST: Java Image Science Toolkit (RRID:SCR_008887) Copy   

•   Source: SciCrunch Registry