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http://www.hpppi.iicb.res.in/btox/

Database of Bacterial ExoToxins for Human is a database of sequences, structures, interaction networks and analytical results for 229 exotoxins, from 26 different human pathogenic bacterial genus. All toxins are classified into 24 different Toxin classes. The aim of DBETH is to provide a comprehensive database for human pathogenic bacterial exotoxins. DBETH also provides a platform to its users to identify potential exotoxin like sequences through Homology based as well as Non-homology based methods. In homology based approach the users can identify potential exotoxin like sequences either running BLASTp against the toxin sequences or by running HMMER against toxin domains identified by DBETH from human pathogenic bacterial exotoxins. In Non-homology based part DBETH uses a machine learning approach to identify potential exotoxins (Toxin Prediction by Support Vector Machine based approach).

Proper citation: DBETH - Database for Bacterial ExoToxins for Humans (RRID:SCR_005908) Copy   

•   Source: SciCrunch Registry

http://mint.bio.uniroma2.it/virusmint/

A virus protein interactions database that collects and annotates all the interactions between human and viral proteins and integrates this information in the human protein interaction network. It uses the PSI-MI standard and is fully integrated with the MINT database. You can search for any viral or human protein by entering either common names or database identifiers or display a complete viral interactome.

Proper citation: VirusMINT (RRID:SCR_005987) Copy   

•   Source: SciCrunch Registry

http://www.gene-regulation.com/pub/databases.html#transfac

Manually curated database of eukaryotic transcription factors, their genomic binding sites and DNA binding profiles. Used to predict potential transcription factor binding sites.

Proper citation: TRANSFAC (RRID:SCR_005620) Copy   

•   Source: SciCrunch Registry

http://omicslab.genetics.ac.cn/GOEAST/

Gene Ontology Enrichment Analysis Software Toolkit (GOEAST) is a web based software toolkit providing easy to use, visualizable, comprehensive and unbiased Gene Ontology (GO) analysis for high-throughput experimental results, especially for results from microarray hybridization experiments. The main function of GOEAST is to identify significantly enriched GO terms among give lists of genes using accurate statistical methods. Compared with available GO analysis tools, GOEAST has the following unique features: * GOEAST supports analysis for data from various resources, such as expression data obtained using Affymetrix, illumina, Agilent or customized microarray platforms. GOEAST also supports non-microarray based experimental data. The web-based feature makes GOEAST very user friendly; users only have to provide a list of genes in correct formats. * GOEAST provides visualizable analysis results, by generating graphs exhibiting enriched GO terms as well as their relationships in the whole GO hierarchy. * Note that GOEAST generates separate graph for each of the three GO categories, namely biological process, molecular function and cellular component. * GOEAST allows comparison of results from multiple experiments (see Multi-GOEAST tool). The displayed color of each GO term node in graphs generated by Multi-GOEAST is the combination of different colors used in individual GOEAST analysis. Platform: Online tool

Proper citation: GOEAST - Gene Ontology Enrichment Analysis Software Toolkit (RRID:SCR_006580) Copy   

•   Source: SciCrunch Registry

http://www.snpedia.com/index.php/SNPedia

Wiki investigating human genetics including information about the effects of variations in DNA, citing peer-reviewed scientific publications. It is used by Promethease to analyze and help explain your DNA. It is based on a wiki model in order to foster communication about genetic variation and to allow interested community members to help it evolve to become ever more relevant. As the cost of genotyping (and especially of fully determining your own genomic sequence) continues to drop, we''''ll all want to know more - a lot more - about the meaning of these DNA variations and SNPedia will be here to help. SNPedia has been launched to help realize the potential of the Human Genome Project to connect to our daily lives and well-being. For more information see the Wikipedia page, http://en.wikipedia.org/wiki/SNPedia * Download URL: http://www.SNPedia.com/index.php/Bulk * Web Service URL: http://bots.SNPedia.com/api.php

Proper citation: SNPedia (RRID:SCR_006125) Copy   

•   Source: SciCrunch Registry

http://cossmos.slu.edu/

Database to search through the nucleic acid structures from the Protein Data Bank and examine structural motifs, including (a)symmetric internal loops, bulge loops, and hairpin loops. They have compiled over 2,000 three-dimensional structures, which can now be searched using different parameters, including PDB information, experimental technique, sequence, and motif type. RNA secondary structure is important for designing therapeutics, understanding protein-RNA binding and predicting tertiary structure of RNA. Several databases and downloadable programs exist that specialize in the three-dimensional (3D) structure of RNA, but none focus specifically on secondary structural motifs such as internal, bulge and hairpin loops. To create the RNA CoSSMos database, 2156 Protein Data Bank (PDB) files were searched for internal, bulge and hairpin loops, and each loop''''s structural information, including sugar pucker, glycosidic linkage, hydrogen bonding patterns and stacking interactions, was included in the database. False positives were defined, identified and reclassified or omitted from the database to ensure the most accurate results possible. Users can search via general PDB information, experimental parameters, sequence and specific motif and by specific structural parameters in the subquery page after the initial search. Returned results for each search can be viewed individually or a complete set can be downloaded into a spreadsheet to allow for easy comparison. The RNA CoSSMos database is updated weekly.

Proper citation: RNA CoSSMos (RRID:SCR_006120) Copy   

•   Source: SciCrunch Registry

http://proportal.mit.edu/

ProPortal is a database containing genomic, metagenomic, transcriptomic and field data for the marine cyanobacterium Prochlorococcus. Our goal is to provide a source of cross-referenced data across multiple scales of biological organization--from the genome to the ecosystem--embracing the full diversity of ecotypic variation within this microbial taxon, its sister group, Synechococcus and phage that infect them. The site currently contains the genomes of 13 Prochlorococcus strains, 11 Synechococcus strains and 28 cyanophage strains that infect one or both groups. Cyanobacterial and cyanophage genes are clustered into orthologous groups that can be accessed by keyword search or through a genome browser. Users can also identify orthologous gene clusters shared by cyanobacterial and cyanophage genomes. Gene expression data for Prochlorococcus ecotypes MED4 and MIT9313 allow users to identify genes that are up or downregulated in response to environmental stressors. In addition, the transcriptome in synchronized cells grown on a 24-h light-dark cycle reveals the choreography of gene expression in cells in a ''natural'' state. Metagenomic sequences from the Global Ocean Survey from Prochlorococcus, Synechococcus and phage genomes are archived so users can examine the differences between populations from diverse habitats. Finally, an example of cyanobacterial population data from the field is included.

Proper citation: ProPortal (RRID:SCR_006112) Copy   

•   Source: SciCrunch Registry

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

A web tool, based on a Hidden Markov Model, capable of predicting the transmembrane beta-strands of the gram-negative bacteria outer membrane proteins, and of discriminating such proteins from water-soluble ones when screening large datasets. The model is trained in a discriminative manner, aiming at maximizing the probability of the correct prediction rather than the likelihood of the sequences. The training is performed on a non-redundant database consisting of 16 outer membrane proteins (OMP''s) with their structures known at atomic resolution. We show that we can achieve predictions at least as good comparing with other existing methods, using as input only the amino-acid sequence, without the need of evolutionary information included in multiple alignments. The method is also powerful when used for discrimination purposes, as it can discriminate with a high accuracy the outer membrane proteins from water soluble in large datasets, making it a quite reliable solution for screening entire genomes. This web-server can help you run a discriminating process on any amino-acid sequence and thereafter localize the transmembrane strands and find the topology of the loops.

Proper citation: PRED-TMBB (RRID:SCR_006190) Copy   

•   Source: SciCrunch Registry

http://www.pedigree-draw.com/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 12,2024. Software application for pedigree drawing (entry from Genetic Analysis Software)

Proper citation: Pedigree-Draw (RRID:SCR_008302) Copy   

•   Source: SciCrunch Registry

https://database.riken.jp/sw/en/The_RIKEN_integrated_database_of_mammals/ria254i/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 16, 2019.
A database that integrates not only RIKEN''''s original large-scale mammalian databases, such as FANTOM, the ENU mutagenesis program, the RIKEN Cerebellar Development Transcriptome Database and the Bioresource Database, but also imported data from public databases, such as Ensembl, MGI and biomedical ontologies. Our integrated database has been implemented on the infrastructure of publication medium for databases, termed SciNetS/SciNeS, or the Scientists'''' Networking System, where the data and metadata are structured as a semantic web and are downloadable in various standardized formats. The top-level ontology-based implementation of mammal-related data directly integrates the representative knowledge and individual data records in existing databases to ensure advanced cross-database searches and reduced unevenness of the data management operations. Through the development of this database, we propose a novel methodology for the development of standardized comprehensive management of heterogeneous data sets in multiple databases to improve the sustainability, accessibility, utility and publicity of the data of biomedical information.

Proper citation: RIKEN integrated database of mammals (RRID:SCR_006890) Copy   

•   Source: SciCrunch Registry

http://ambermd.org/

Software package of molecular simulation programs. It is distributed into AmberTools15 and Amber14. AmberTools15 is a software package which can carry out complete molecular dynamics simulations with either explicit water or generalized Born solvent models. It is distributed in source code format and must be compiled in order to be used. Amber14 builds on AmberTools15 by adding the pmemd program, which provides better performance on multiple CPUs and dramatic speed improvements on GPUs compared to sander (molecular dynamics). GPU info, manuals, and tutorials are available on the website.

Proper citation: Assisted Model Building with Energy Refinement (AMBER) (RRID:SCR_014230) Copy   

•   Source: SciCrunch Registry

https://github.com/MikkelSchubert/paleomix

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software toolkit for the processing of ancient and modern HTS data. PALEOMIX also aids in metagenomic analysis of the extracts from the HTS processing.

Proper citation: PALEOMIX (RRID:SCR_015057) Copy   

•   Source: SciCrunch Registry

https://nels.bioinfo.no

Web portal for the administration of Norwegian e-Infrastructure for Life Sciences. Enables Norwegian life scientists and their international collaborators to store, share, archive, and analyse their genomics scale data. NeLS is one of the packages of the ELIXIR.NO project.

Proper citation: NeLS (RRID:SCR_016301) Copy   

•   Source: SciCrunch Registry

https://web.stanford.edu/group/pritchardlab/structure.html

Software package for using multi locus genotype data to investigate population structure. Used for inferring presence of distinct populations, assigning individuals to populations, studying hybrid zones, identifying migrants and admixed individuals, and estimating population allele frequencies in situations where many individuals are migrants or admixed. Can be applied to most of commonly used genetic markers, including SNPS, microsatellites, RFLPs and Amplified Fragment Length Polymorphisms.

Proper citation: STRUCTURE (RRID:SCR_017637) Copy   

•   Source: SciCrunch Registry

https://github.com/Brazelton-Lab/seq-annot

Software Python package for annotating and counting genomic features in genomes and metagenomes. Software tools to facilitate annotation and comparison of genomes and metagenomes.

Proper citation: seq-annot (RRID:SCR_018731) Copy   

•   Source: SciCrunch Registry

https://qupath.github.io/

Open Source software package for digital pathology image analysis. Used for whole slide image analysis and digital pathology. Provides researchers with batch processing and scripting functionality, and extensible platform with which to develop and share new algorithms to analyze complex tissue images.

Proper citation: QuPath (RRID:SCR_018257) Copy   

•   Source: SciCrunch Registry

https://chlorobox.mpimp-golm.mpg.de/geseq.html

Software tool for rapid and accurate annotation of organelle genomes, in particular chloroplast genomes.

Proper citation: GeSeq (RRID:SCR_017336) Copy   

•   Source: SciCrunch Registry

https://metacpan.org/dist/Bio-EUtilities

Software package which interacts with and retrieves data from NCBI's eUtils. This distribution encompasses low-level API for interacting with (and storing) information from NCBI's eUtils interface. See Bio::DB::EUtilities for the query API to retrieve data from NCBI, and Bio::Tools::EUtilities for the general class storage system. Note this may change to utilize the XML schema for each class at some point, though we will attempt to retain current functionality for backward compatibility unless this becomes problematic.

Proper citation: Bio-EUtilities (RRID:SCR_024064) Copy   

•   Source: SciCrunch Registry

https://metacpan.org/dist/Bio-Tools-Run-Alignment-Clustalw

Software package for performing multiple sequence alignment from set of unaligned sequences and/or sub-alignments by means of the clustalw program.

Proper citation: Bio-Tools-Run-Alignment-Clustalw (RRID:SCR_024067) Copy   

•   Source: SciCrunch Registry

https://sourceforge.net/projects/tab2mage/

Software package written and supported by the ArrayExpress curation team, which aims to ease the process of submitting large microarray experiment datasets.Tab2MAGE uses flexible spreadsheet format for MIAME annotation of microarray experiments.Spreadsheets may be submitted directly to ArrayExpress, or used to generate MAGE-ML for data exchange.

Proper citation: Tab2MAGE (RRID:SCR_024101) Copy   

•   Source: SciCrunch Registry