Tools   Select Another Resource Report Type

http://db-mml.sjtu.edu.cn/ICEberg/

ICEberg is an integrated database that provides comprehensive information about integrative and conjugative elements (ICEs) found in bacteria. ICEs are conjugative self-transmissible elements that can integrate into and excise from a host chromosome. An ICE contains three typical modules, integration and excision, conjugation, and regulation modules, that collectively promote vertical inheritance and periodic lateral gene flow. Many ICEs carry likely virulence determinants, antibiotic-resistant factors and/or genes coding for other beneficial traits. ICEberg offers a unique, highly organized, readily explorable archive of both predicted and experimentally supported ICE-relevant data. It currently contains details of 428 ICEs found in representatives of 124 bacterial species, and a collection of >400 directly related references. A broad range of similarity search, sequence alignment, genome context browser, phylogenetic and other functional analysis tools are readily accessible via ICEberg. ICEberg will facilitate efficient, multidisciplinary and innovative exploration of bacterial ICEs and be of particular interest to researchers in the broad fields of prokaryotic evolution, pathogenesis, biotechnology and metabolism. The ICEberg database will be maintained, updated and improved regularly to ensure its ongoing maximum utility to the research community.

Proper citation: ICEberg (RRID:SCR_006026) Copy   

•   Source: SciCrunch Registry

https://www.genome.wisc.edu/tools/asap.htm

Database and web interface developed to store, update and distribute genome sequence data and gene expression data. ASAP was designed to facilitate ongoing community annotation of genomes and to grow with genome projects as they move from the preliminary data stage through post-sequencing functional analysis. The ASAP database includes multiple genome sequences at various stages of analysis, and gene expression data from preliminary experiments. Use of some of this preliminary data is conditional, and it is the users responsibility to read the data release policy and to verify that any use of specific data obtained through ASAP is consistent with this policy. There are four main routes to viewing the information in ASAP: # a summary page, # a form to query the genome annotations, # a form to query strain collections, and # a form to query the experimental data. Navigational buttons appear on every page allowing users to jump to any of these four points., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ASAP (RRID:SCR_001849) Copy   

•   Source: SciCrunch Registry

http://genomics1.mh-hannover.de/genometa/index.php?Site=Home

A Java based bioinformatics program which allows rapid analysis of metagenomic short read datasets. Millions of short reads can be accurately analysed within minutes and visualised in the browser component. A large database of diverse bacteria and archaea has been constructed as a reference sequence. The approach is based upon the established open source visualisation tool IGB and supported by the rapid alignment program bowtie. The Picard toolset for SAM files is also made use of.

Proper citation: Genometa (RRID:SCR_001181) Copy   

•   Source: SciCrunch Registry

http://bix.ucsd.edu/projects/singlecell/

Software package for short read data from single cells that improves assembly through use of progressively increasing coverage cutoff. Used for single cell Illumina sequences, allows variable coverage datasets to be utilized with assembly of E. coli and S. aureus single cell reads. Assembles single cell genome of uncultivated SAR324 clade of Deltaproteobacteria.

Proper citation: Velvet-SC (RRID:SCR_004377) Copy   

•   Source: SciCrunch Registry

https://computation-rnd.llnl.gov/lmat/

Open-source software tool to assign taxonomic labels to as many reads as possible in very large metagenomic datasets and report the taxonomic profile of the input sample. The quick "single pass" analysis of every read allows read binning to support additional more computationally expensive analysis such as metagenomic assembly or sensitive database searches on targeted subsets of reads.

Proper citation: LMAT (RRID:SCR_004646) Copy   

•   Source: SciCrunch Registry

http://huttenhower.sph.harvard.edu/metaphlan2

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Computational tool for profiling the composition of microbial communities from metagenomic shotgun sequencing data. It relies on unique clade-specific marker genes identified from reference genomes.

Proper citation: MetaPhlAn (RRID:SCR_004915) Copy   

•   Source: SciCrunch Registry

http://www.clipz.unibas.ch/downloads/TSSer/index.php

A computational pipeline to analyze differential RNA sequencing (dRNA-seq) data to determine transcription start sites genome-wide.

Proper citation: TSSer (RRID:SCR_006419) Copy   

•   Source: SciCrunch Registry

http://www.brc.riken.jp/inf/en

RIKEN BRC contributes to advancement of life science research by collecting, preserving and distributing biological resources such as experimental animals, experimental plants, cultured cell lines, genetic materials (DNA), and associated bioinformatics. The RIKEN BRC develops novel bioresources to promote scientific research and new technologies to increase the value of bioresources, and also to implement effective procedures for the preservation, quality control and usage of bioresources. The RIKEN BRC is working closely with institutions in Japan and abroad.

Proper citation: RIKEN BioResource Center (RRID:SCR_003250) Copy   

•   Source: SciCrunch Registry

http://iimcb.genesilico.pl/MetaLocGramN/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023.A tool for subcellular localization prediction of Gram-negative proteins. You can also use MetaGramLocN via SOAP. SOAP enables you to invoke our method from scripts written in your programming language of choice.

Proper citation: MetaLocGramN (RRID:SCR_003154) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/intact

Open source database system and analysis tools for molecular interaction data. All interactions are derived from literature curation or direct user submissions. Direct user submissions of molecular interaction data are encouraged, which may be deposited prior to publication in a peer-reviewed journal. The IntAct Database contains (Jun. 2014): * 447368 Interactions * 33021 experiments * 12698 publications * 82745 Interactors IntAct provides a two-tiered view of the interaction data. The search interface allows the user to iteratively develop complex queries, exploiting the detailed annotation with hierarchical controlled vocabularies. Results are provided at any stage in a simplified, tabular view. Specialized views then allows "zooming in" on the full annotation of interactions, interactors and their properties. IntAct source code and data are freely available.

Proper citation: IntAct (RRID:SCR_006944) Copy   

•   Source: SciCrunch Registry

http://deconseq.sourceforge.net/

Software tool to automatically detect and efficiently remove sequence contaminations from genomic and metagenomic datasets. It is easily configurable and provides a user-friendly interface. The user can upload FASTA or FASTQ files and select the databases used for contamination screening, including seven human genomes, bacterial genomes, and viral genomes. The user can set the thresholds interactivly and see the results directly using the functionality of the graphical interface. The results can be downloaded in joined or separated files in different formats. The coverage-identity plots provide additional information that can guide the selections of the thresholds using color coded points and connecting lines.

Proper citation: DeconSeq (RRID:SCR_007006) Copy   

•   Source: SciCrunch Registry

http://www.dnaftb.org/dnaftb/

An animated primer on the basics of DNA, genes, and heredity organized around three key concepts: Classical Genetics, Molecules of Genetics, and Genetic Organization and Control. The science behind each concept is explained by: animation, image gallery, video interviews, problem, biographies, and links.

Proper citation: DNA From The Beginning: AN Animated Primer on the Basics of DNA, Genes, and Heredity (RRID:SCR_008028) Copy   

•   Source: SciCrunch Registry

http://aps.unmc.edu/AP/main.php

Database and data analysis system dedicated to glossary, nomenclature, classification, information search, prediction, design, and statistics of Antimicrobial peptides and beyond. The peptide data stored in the APD were gleaned from the literature (PubMed, PDB, Google, and Swiss-Prot) manually in the past several years. Peptides will be registered into this database if: # they are from natural sources (bacteria, protozoa, fungi, plants, and animals); # their antimicrobial activities are demonstrated (MIC

Proper citation: APD (RRID:SCR_006606) Copy   

•   Source: SciCrunch Registry

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

Database of related protein sequences (clusters) consisting of proteins derived from the annotations of whole genomes, organelles and plasmids. It currently limited to Archaea, Bacteria, Plants, Fungi, Protozoans, and Viruses. It contains annotation information, publications, domains, structures, and external links and analysis tools including multiple alignments, phylogenetic trees, and genomic neighborhoods (ProtMap). Data is available for download via Protein Clusters FTP

Proper citation: Protein Clusters (RRID:SCR_003459) Copy   

•   Source: SciCrunch Registry

http://biocomputer.bio.cuhk.edu.hk/T3DB/

Database aimed to annotate all bacterial Type III Secretion System (T3SS) related structure, effector, regulator, and auxiliary genes.

Proper citation: Type-III-Secretion-System related database (RRID:SCR_002941) Copy   

•   Source: SciCrunch Registry

http://nbc.ece.drexel.edu/

Webserver for taxonomic classification of metagenomic reads.

Proper citation: NBC (RRID:SCR_004772) Copy   

•   Source: SciCrunch Registry

https://digestivediseasescenters.org/content/ddrc-uab-genetically-defined-microbe-core

Core composed of the Viral Unit, which provides labeled andn unlabeled viral components, and Bacterial Unit, which provides bacteria and bacterial proteins for research. The retroviral unit focues on the viral components of the retrovirus HIV-1.

Proper citation: Mucosal HIV and Immunobiology Center Genetically-Defined Microbe Core (RRID:SCR_015262) Copy   

•   Source: SciCrunch Registry

http://www.homd.org/index.php

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on April 14,2022. Database of comprehensive information on the approximately 600 prokaryote species that are present in the human oral cavity. The majority of these species are uncultivated and unnamed, recognized primarily by their 16S rRNA sequences. The HOMD presents a provisional naming scheme for the currently unnamed species so that strain, clone, and probe data from any laboratory can be directly linked to a stably named reference entity. The HOMD links sequence data with phenotypic, phylogenetic, clinical, and bibliographic information. Full and partial oral bacterial genome sequences determined as part of this project and the Human Microbiome Project, are being added to the HOMD as they become available. HOMD offers easy to use tools for viewing all publicly available oral bacterial genomes. Data is also downloadable.

Proper citation: HOMD (RRID:SCR_012770) Copy   

•   Source: SciCrunch Registry

http://www.jcvi.org/mpidb

Database that collects and provides all known physical microbial interactions. Currently, 24,295 experimentally determined interactions among proteins of 250 bacterial species/strains can be browsed and downloaded. These microbial interactions have been manually curated from the literature or imported from other databases (IntAct, DIP, BIND, MINT) and are linked to 26,578 experimental evidences (PubMed ID, PSI-MI methods). In contrast to these databases, interactions in MPIDB are further supported by 68,346 additional evidences based on interaction conservation, co-purification, and 3D domain contacts (iPfam, 3did). (spoke/matrix) binary interactions inferred from pull-down experiments are not included.

Proper citation: MPIDB (RRID:SCR_001898) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.biol.uoa.gr/PRED-LIPO/

A web tool using the Hidden Markov Model method for the prediction of lipoprotein signal peptides of Gram-positive bacteria, trained on a set of 67 experimentally verified lipoproteins. The method outperforms LipoP and the methods based on regular expression patterns, in various data sets containing experimentally characterized lipoproteins, secretory proteins, proteins with an N-terminal TM segment and cytoplasmic proteins. The method is also very sensitive and specific in the detection of secretory signal peptides and in terms of overall accuracy outperforms even SignalP, which is the top-scoring method for the prediction of signal peptides.

Proper citation: PRED-LIPO (RRID:SCR_006187) Copy   

•   Source: SciCrunch Registry